io.github.LuxAlgo/luxalgo-mcp-server

Est-ce que io.github.LuxAlgo/luxalgo-mcp-server est sûr ?

Au dernier audit MCP Hub, le serveur MCP « io.github.LuxAlgo/luxalgo-mcp-server » est classé « Non encore testé ». Référencé dans l'annuaire. Seul le pentest comportemental fait foi, et il n'a pas encore été exécuté sur ce serveur. Le verdict est réévalué en continu ; consultez la fiche pour l'état à jour.

Méthode : MCP Hub analyse la description de chaque outil (couche 1) et, pour le verdict fort, exécute le serveur dans une micro-VM isolée avec leurres et réseau bloqué (couche 2). On publie des noms et des compteurs, jamais le contenu brut renvoyé par un outil.

Les 42 outils

• edge_presets≈ 349 tokens

  The catalog of session-statistics questions the hosted store precomputes nightly — gap fills, opening-range breakouts, day-of-week effects, event-day behavior, and more. Each preset states in plain language what its number means. Returns preset ids for edge_report.

  Paramètres, retour & exemple (2)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • category · string · optionnel
    Narrow to one category (the result lists all categories)

  Exemple d'appel

  {"name": "edge_presets", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• edge_report≈ 435 tokens

  One precomputed session-statistics result: P(outcome | conditions) for a preset on a hosted symbol, in the engine's full honesty envelope — the estimate with N and a Wilson 95% confidence interval, minimum-sample guards, a first-half vs second-half stability split, per-year counts, the value distribution where the outcome is continuous, and the disclaimer. Historical conditional frequencies, not predictions. Preset ids come from edge_presets; symbols from edge_symbols.

  Paramètres, retour & exemple (3)

  Paramètres

  • preset · string · requis
    Preset id, e.g. 'gap-fill' — see edge_presets
  • symbol · string · requis
    Hosted symbol, e.g. 'BTCUSDT' — see edge_symbols
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "edge_report", "arguments": {"preset": "texte", "symbol": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• edge_symbols≈ 356 tokens

  What the hosted Edge Stats store covers: the symbols, their session calendars, coverage windows, session counts, and when the nightly build last ran. Session statistics (how often a setup actually worked, with sample sizes and confidence intervals) come from the open-source edge-stats engine over free market data. Start here, then edge_presets for the questions you can ask, then edge_report for a result.

  Paramètres, retour & exemple (1)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "edge_symbols", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_add_trade≈ 732 tokens

  Log a trade by adding its fills to a `manual` or `import` journal account (never a broker-synced one — the sync owns those). The journal derives trades from fills: a long round trip is a buy fill then a sell fill, a short is sell then buy, scale-ins and partial exits are just more fills, and a lone fill opens a position. Times are ISO 8601 instants with offset; fees are per fill. Fills identical to existing ones are skipped as duplicates. Returns the insert counts and the trade(s) the fills now belong to, with `key`s for journal_update_trade. Correcting or removing an existing fill is done in the app, not here. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (3)

  Paramètres

  • fills · array · requis
    The fills, in any order.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accountId · string · requis
    A `manual` or `import` account id from journal_list_accounts.

  Exemple d'appel

  {"name": "journal_add_trade", "arguments": {"fills": [], "context": "texte", "accountId": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_breakdown≈ 570 tokens

  Where the P&L actually comes from: closed trades in the window grouped nine ways — weekday, time of day, hold time, symbol, side, position size, tag, rating and asset class — each group with trade count, wins, losses, net P&L, average net P&L and win rate (breakevens excluded). Defaults to all time, since groups need sample size; narrow with `range` or `from`/`to`. The tool for 'what am I good or bad at' questions; journal_overview has the headline numbers. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (5)

  Paramètres

  • to · string · optionnel
    Inclusive end day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • from · string · optionnel
    Inclusive start day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • range · string · optionnel · today | 7d | 30d | 90d | 365d | ytd | all
    Named window ending today in the journal timezone. Ignored when from/to are given.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_breakdown", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_calendar≈ 459 tokens

  One month of the P&L calendar: week rows of day cells (net and gross P&L, fees, trade/win/loss/breakeven counts, volume; null for days with no trades), each week's net P&L and trade count, and the month's net P&L, trade count, trading days and winning days. Days are in the journal timezone. Omit `month` for the current month. Drill into one day with journal_get_day. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (3)

  Paramètres

  • month · string · optionnel
    Month as YYYY-MM. Default: the current month in the journal timezone.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_calendar", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_get_day≈ 441 tokens

  A single trading day: its stats (null when nothing traded), its trades (closed that day, or opened that day and still open) as summaries, and the day's notes with their ids. `date` is a YYYY-MM-DD day key in the journal timezone. Use it for 'how did Tuesday go', and to find note ids for journal_update_note. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (3)

  Paramètres

  • date · string · requis
    The day, YYYY-MM-DD in the journal timezone.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_get_day", "arguments": {"date": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_get_trade≈ 427 tokens

  One trade in full: the summary fields plus its fills (each with the effective values, what the source reported, the user's corrections and whether it is hidden), per-exit gross P&L, hidden fills inside the trade's span, and every annotation — notes, tags, mistakes, playbook id, stop loss, profit target, review time. Use after journal_list_trades or journal_get_day when the user asks about a specific trade or before annotating it. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (2)

  Paramètres

  • key · string · requis
    The trade's `key` exactly as returned by journal_list_trades, journal_get_day, journal_search_notes or journal_add_trade. Never construct one.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "journal_get_trade", "arguments": {"key": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_list_accounts≈ 400 tokens

  The signed-in user's trade-journal accounts — id, name, broker, kind (`sync` mirrors a live broker connection, `import` came from statements, `manual` is hand-entered), currency, initial balance, P&L lot method, last broker sync, archived state — plus `timeZone`, the journal timezone every date in the journal tools is expressed in. Call this first: every other journal tool's `accounts` filter takes these ids and rejects unknown ones, and journal_add_trade needs a `manual` or `import` account. An empty list means no journal yet. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (1)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "journal_list_accounts", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_list_tags≈ 426 tokens

  The user's annotation vocabulary: every tag, mistake and playbook id they have put on any trade (open or closed), most-used first with the number of trades carrying each. Check it before journal_update_trade so new annotations reuse the user's own words instead of minting near-duplicates. Per-trade tags are on each trade summary, not here. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (2)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_list_tags", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_list_trades≈ 962 tokens

  Trade summaries — `key`, account, symbol, asset class, direction, status (open/win/loss/breakeven), open and close times, quantity and open quantity, average entry/exit, gross and net P&L, fees, fill count, duration, realized R, tags, rating, reviewed flag, hasNotes — newest-opened first by default. `sort` orders by any of openedAt, closedAt, netPnl, grossPnl, durationMs, quantity, symbol or rating (names match the response fields); `order` is desc unless set, except symbol which defaults to asc. Trades lacking the sort value (open trades for closedAt/durationMs, unrated for rating) come last in either order; netPnl is after fees, grossPnl before. Filter by account ids, open-day window (`from`/`to` are inclusive YYYY-MM-DD day keys in the journal timezone, applied to the trade's open day; open positions are always listed), symbol, direction, status or one exact tag. Keyset-paginated: pass `nextCursor` back as `cursor` with the same sort, order and filters. Examples: biggest winners this month = from/to + sort netPnl; worst by gross = sort grossPnl, order asc, status loss; longest holds = sort durationMs. Summaries carry no fills or note text: journal_get_trade with the `key` has those. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (12)

  Paramètres

  • to · string · optionnel
    Inclusive end day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • tag · string · optionnel
    Trades carrying exactly this tag (see journal_list_tags).
  • from · string · optionnel
    Inclusive start day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • sort · string · optionnel · openedAt | closedAt | netPnl | grossPnl | durationMs | quantity | symbol | rating
    Field to order by; default openedAt. Trades without a value for it come last in either order.
  • limit · integer · optionnel
    Page size, default 25.
  • order · string · optionnel · asc | desc
    Default desc (largest / latest first); symbol defaults to asc (A→Z).
  • cursor · string · optionnel
    `nextCursor` from the previous page; keep every other argument identical.
  • status · string · optionnel · open | win | loss | breakeven
  • symbol · string · optionnel
    One symbol, e.g. 'AAPL' (case-insensitive).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.
  • direction · string · optionnel · long | short

  Exemple d'appel

  {"name": "journal_list_trades", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_overview≈ 703 tokens

  The journal dashboard in one call for a window: performance metrics (net/gross P&L, fees, win rate, day win rate, profit factor, expectancy, average win/loss and their ratio, largest win/loss, streaks, max drawdown, recovery factor, profit concentration, average realized R), the Edge Score with its six components, per-day P&L stats, the cumulative equity curve, open positions, and the accounts and settings the numbers cover. Closed trades bucket by close day in the journal timezone; open positions count toward any window that reaches today. `compare: true` adds `previous` — the equal-length window just before. Defaults to the last 30 days; pass `range: 'all'` or explicit `from`/`to` for more. Null metrics are not computable yet (e.g. no losses → `profitFactorIsInfinite`). Use journal_breakdown for where the P&L comes from and journal_list_trades for the trades themselves. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (6)

  Paramètres

  • to · string · optionnel
    Inclusive end day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • from · string · optionnel
    Inclusive start day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • range · string · optionnel · today | 7d | 30d | 90d | 365d | ytd | all
    Named window ending today in the journal timezone. Ignored when from/to are given.
  • compare · boolean · optionnel
    Also compute the equal-length window immediately before this one.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_overview", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_search_notes≈ 634 tokens

  Search the notes feed — day notes and trades that carry notes — newest first as one stream split by kind: `notes` (day notes, with ids for journal_update_note) and `tradeNotes` (the trade summary with its note text; annotate via journal_update_trade). Filter by case-insensitive text (`q`), day-key window, symbol (trade notes only — day notes have no symbol and drop out) and account ids; keyset-paginated via `cursor`/`nextCursor`. Omit every filter for the latest notes. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (8)

  Paramètres

  • q · string · optionnel
    Substring to look for in note text, case-insensitive.
  • to · string · optionnel
    Inclusive end day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • from · string · optionnel
    Inclusive start day (YYYY-MM-DD, journal timezone). Overrides `range`.
  • limit · integer · optionnel
    Page size, default 25.
  • cursor · string · optionnel
    `nextCursor` from the previous page; keep every other argument identical.
  • symbol · string · optionnel
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • accounts · array · optionnel
    Journal account ids to scope to (from journal_list_accounts). Omit for every account, archived ones included. Unknown ids are rejected.

  Exemple d'appel

  {"name": "journal_search_notes", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_update_note≈ 455 tokens

  Replace a day note's text and/or move it to another day, by note id (from journal_get_day or journal_search_notes). The body is replaced whole — to append, read the current text first and send the full new version. Trade notes are edited with journal_update_trade, not here. Returns the updated note. Day notes in the LuxAlgo journal: https://docs.luxalgo.com/platform/workspaces/journal/notes Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (4)

  Paramètres

  • body · string · optionnel
    The full new text.
  • date · string · optionnel
    Move the note to this day, YYYY-MM-DD in the journal timezone.
  • noteId · string · requis
    The note's `id`.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "journal_update_note", "arguments": {"noteId": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_update_trade≈ 949 tokens

  Annotate a trade — the user-owned fields only: `notes` (free text about this trade), `tags`, `mistakes`, `playbookId`, `rating` 1–5, `stopLoss` and `profitTarget` (price levels; the stop is what realized R is measured against) and `reviewed`. `tags`/`mistakes` replace the whole list; use `addTags`/`removeTags`/`addMistakes`/`removeMistakes` to change a few entries without clobbering the rest (check journal_list_tags for the user's existing words). Pass null to clear a field. Does not touch fills, prices or P&L — those derive from the fills. Returns the updated trade in full. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (14)

  Paramètres

  • key · string · requis
    The trade's `key` exactly as returned by journal_list_trades, journal_get_day, journal_search_notes or journal_add_trade. Never construct one.
  • tags · ? · optionnel
  • notes · ? · optionnel
    Replaces the trade's note text; null clears it.
  • rating · ? · optionnel
    Execution quality 1–5; null clears it.
  • addTags · array · optionnel
    Tags to add (existing ones are kept; case-insensitive duplicates are ignored).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • mistakes · ? · optionnel
  • reviewed · boolean · optionnel
    Mark the trade reviewed (true) or not (false).
  • stopLoss · number|null · optionnel
    Planned stop price; null clears it.
  • playbookId · ? · optionnel
    Playbook / setup name this trade followed; null clears it.
  • removeTags · array · optionnel
    Tags to remove (case-insensitive).
  • addMistakes · array · optionnel
    Mistakes to add.
  • profitTarget · number|null · optionnel
    Planned target price; null clears it.
  • removeMistakes · array · optionnel
    Mistakes to remove (case-insensitive).

  Exemple d'appel

  {"name": "journal_update_trade", "arguments": {"key": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• journal_write_note≈ 440 tokens

  Add a new note to a trading day — any day, traded or not; `date` is YYYY-MM-DD in the journal timezone. Days hold any number of notes, so this never overwrites: to change an existing note use journal_update_note, and for a note about one specific trade use journal_update_trade's `notes`. Returns the note with its id. Day notes in the LuxAlgo journal: https://docs.luxalgo.com/platform/workspaces/journal/notes Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (3)

  Paramètres

  • body · string · requis
    The note text (plain text or markdown).
  • date · string · requis
    The day the note belongs to, YYYY-MM-DD in the journal timezone.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "journal_write_note", "arguments": {"body": "texte", "date": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_get_concept≈ 359 tokens

  Explain a trading concept: the Library's full write-up as markdown — definition, formula, how traders read it, and its indicator implementations. Use for any 'what is X / how does X work' question. Needs the exact slug — find it with library_search or library_list_concepts.

  Paramètres, retour & exemple (2)

  Paramètres

  • slug · string · requis
    Exact concept slug, e.g. 'rsi' or 'order-blocks' — from search or list results
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_get_concept", "arguments": {"slug": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_get_family≈ 392 tokens

  A family's hub page as markdown — the written overview of that school of analysis plus its complete concept roster. Use after library_list_families, or when the user asks about a whole area like 'SMC' or 'Wyckoff'.

  Paramètres, retour & exemple (2)

  Paramètres

  • key · string · requis · trend | momentum | volatility | volume-orderflow | market-structure | smc-ict | wyckoff | elliott-harmonics
    Family key, e.g. 'smc-ict'
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_get_family", "arguments": {"key": "trend", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_get_indicator≈ 341 tokens

  Details for one indicator: what it does, how to read it, family, concept links, preview image — plus whether its source code is available (fetch the code itself with library_get_source_code). Use when the user asks about a specific indicator.

  Paramètres, retour & exemple (2)

  Paramètres

  • slug · string · requis
    Indicator slug, e.g. 'tri-star'
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_get_indicator", "arguments": {"slug": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_get_source_code≈ 329 tokens

  The full, working source code of a Library indicator (works on TradingView). Kept separate from library_get_indicator because sources are long — call it only when the user wants the code itself.

  Paramètres, retour & exemple (2)

  Paramètres

  • slug · string · requis
    Indicator slug
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_get_source_code", "arguments": {"slug": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_list_concepts≈ 431 tokens

  Browse every trading and technical-analysis concept in the Library — paginated, optionally one family. Use to enumerate a topic area or find slugs for library_get_concept; for keyword lookup prefer library_search.

  Paramètres, retour & exemple (4)

  Paramètres

  • page · integer · optionnel
    Default 0
  • family · string · optionnel · trend | momentum | volatility | volume-orderflow | market-structure | smc-ict | wyckoff | elliott-harmonics
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • page_size · integer · optionnel
    Default 50

  Exemple d'appel

  {"name": "library_list_concepts", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_list_families≈ 300 tokens

  The Library's top-level taxonomy: 17 families of trading concepts (trend, momentum, SMC/ICT, statistics, …) with concept counts and hub links. The natural first call for orientation.

  Paramètres, retour & exemple (1)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_list_families", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_list_indicators≈ 669 tokens

  Browse the indicator catalog with filters and server-side sorting (newest first by default). Filter by family, concept slug (implementations of one concept), tags (ids from library_list_tags, AND-combined), trading platform, or plan tier. Use for structured browsing — 'latest indicators', 'everything in the volatility family', 'indicators implementing liquidity sweeps'; for keyword discovery prefer library_search.

  Paramètres, retour & exemple (11)

  Paramètres

  • page · integer · optionnel
    Default 0
  • sort · string · optionnel · name | date | family
    Default: date
  • tags · array · optionnel
    Tag ids (from library_list_tags); an indicator must carry every tag
  • text · string · optionnel
    Server-side text filter
  • tier · string · optionnel · essential | premium | ultimate | ultra
    Only indicators included in this LuxAlgo plan tier
  • family · string · optionnel · trend | momentum | volatility | volume-orderflow | market-structure | smc-ict | wyckoff | elliott-harmonics
  • concept · string · optionnel
    Concept slug — only indicators linked to this concept, e.g. 'rsi'
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • platform · string · optionnel
    Trading platform the indicator supports, e.g. 'metatrader'
  • direction · string · optionnel · asc | desc
  • page_size · integer · optionnel
    Default 24

  Exemple d'appel

  {"name": "library_list_indicators", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_list_tags≈ 312 tokens

  The Library's indicator tag vocabulary (behavioral traits like 'Volatility', 'Trailing-Stop', 'Repainting Functionality'). Returns ids to pass as the tags filter of library_list_indicators — tags are orthogonal to the concept-family taxonomy.

  Paramètres, retour & exemple (1)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_list_tags", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• library_search≈ 536 tokens

  Search the LuxAlgo Library — the encyclopedia of trading and technical analysis. One query over 800+ concepts (alias-aware: 'stochastics' finds Stochastic Oscillator) and 800+ ready-to-use indicators. Start here whenever you have a name, informal term, or topic; results carry slugs for the get tools plus canonical URLs for citation.

  Paramètres, retour & exemple (5)

  Paramètres

  • type · string · optionnel · all | concepts | indicators
    Limit to 'concepts' (explanations) or 'indicators' (implementations); default all
  • limit · integer · optionnel
    Max results (default 10)
  • query · string · requis
    A concept, indicator name, alias, or topic — e.g. 'order blocks', 'mean reversion', 'stochastics'
  • family · string · optionnel · trend | momentum | volatility | volume-orderflow | market-structure | smc-ict | wyckoff | elliott-harmonics
    Narrow to one concept family
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "library_search", "arguments": {"query": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• luxalgo_account≈ 325 tokens

  The signed-in user's LuxAlgo account: plan tier, entitlements (limits such as alerts, historical bars, AI credits) and profile basics. Use it to tailor answers to what the user's plan actually allows, or when the user asks what plan they are on. Requires signing in with a LuxAlgo account (OAuth).

  Paramètres, retour & exemple (1)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "luxalgo_account", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_challenge_rules≈ 1242 tokens

  Fetch one directory challenge's complete ruleset (ChallengeSpec), adapted from the live LuxAlgo directory: evaluation steps (profit targets in percent units of the initial account, minimum trading days, time limits); the daily-loss rule with its exact semantics (basis = measured from prior-day balance vs prior-day equity; limitBasis = whether a pct limit is a fixed allowance of the initial balance or recomputed daily from the anchor; evaluation = breached on an intraday touch vs only at the close; includesOpenPnl = whether floating P&L can breach it); the max-loss rule and its drawdown mode (How the max-loss floor behaves - the single most consequential rule difference between firms. 'static-initial': floor fixed at initial balance minus the limit; never moves (classic CFD two-step). 'trailing-realized-eod': floor ratchets up with end-of-day balance highs; intraday highs do not move it. 'trailing-intraday-unrealized': floor trails the peak unrealized equity intraday and never stops trailing (futures-style; the most-miscalculated rule in the industry: it cuts pass probability dramatically). 'trailing-locks-at-initial': trails intraday peak equity until the floor reaches the initial balance, then freezes (common futures variant). Locking is also composable: locksAtInitial adds the same lock to an EOD trail, and lockOffsetAmount shifts the lock level to initial balance + that amount (e.g. 100 models 'stops trailing $100 above the start').); per-step consistency rules (steps[].consistency.maxBestDayProfitPct - SIMULATED: one outsized day effectively raises the target until the best-day share complies); fees (price, one-time vs monthly billing, reset fee, activation fee, refundable-on-pass); funded terms (profit split percent, payout frequency, first-payout minimum days, and funded.payoutRules - SIMULATED payout gating: minWinningDays, winningDayMinProfit, per-payout caps maxPayoutPctOfProfit/maxPayoutAmount, bufferAmount, and a windowed consistencyMaxBestDayPct gate); flagsNotSimulated (rules the entry declares but the engine does not simulate - material caveats to relay to the user); and sources (the firm-page citation when the directory serves one). The result also carries `provenance` and `inferredFields` - every rule read from free text instead of a structured column is named there; relay them and treat the firm's page as authoritative. The returned `challenge` object is exactly the shape the simulation tools accept as inline `spec`: copy it, change a rule, and re-simulate to quantify how a rule variation moves pass probability and EV. UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DATA SOURCE & PROVENANCE: firm data comes live from LuxAlgo's public, keyless prop-firm directory API - the data behind luxalgo.com/prop-firms. Rule semantics are used verbatim where the directory serves structured rule columns; where it serves only free text, semantics are inferred ONLY when one reasonable reading exists, and every inferred field is disclosed in `inferredFields` (provenance 'directory+inferred') - relay those to the user next to any numbers. Challenges whose loss rules cannot be established are refused as not simulatable rather than guessed. Firms change rules; each firm's own page is always authoritative. NOTE: this returns the simulatable encoding of one challenge's rules; the directory listing with every captured field, plus live offers, is propfirms_get and propfirms_search_challenges.

  Paramètres, retour & exemple (3)

  Paramètres

  • firmId · string · requis
    Directory firm id or firm name from propfirms_list_simulatable, e.g. 'ftmo'.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • challengeId · string · requis
    Directory challenge id from propfirms_list_simulatable.

  Exemple d'appel

  {"name": "propfirms_challenge_rules", "arguments": {"firmId": "texte", "context": "texte", "challengeId": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_compare≈ 6751 tokens

  Simulate the SAME trader across several challenges (directory references and/or inline specs, up to 12) under identical options and seed, and return one row per challenge sorted by expected value. THIS IS NOT A RANKING: rows are ordered by EV for the caller's specific inputs - trader stats, risk sizing, and options - and a different trader profile reorders them. The tool computes data for the user's own decision; it implies no endorsement, league table, or recommendation of any firm, and results should be presented that way ('best EV for these inputs', never 'best firm'). Each row carries perAttemptPassProbability, fundedProbability, expectedAttempts, expectedCost, evTotal, pEvPositive, daysToFundedP50, and the challenge's flagsNotSimulated - challenges with more unsimulated rules have optimistic numbers, so compare flags alongside EV, not EV alone. Consistency rules and funded payout gating ARE simulated (engine v1), so EV already reflects them where a ruleset has them. For full per-challenge distributions run propfirms_simulate on the interesting rows. UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises.

  Paramètres, retour & exemple (16)

  Paramètres

  • seed · ? · optionnel
    RNG seed (integer or string). Default 42. Same inputs + seed reproduce byte-identical results - include the seed when reporting so users can reproduce the numbers.
  • paths · integer · optionnel
    Monte Carlo paths (independent simulated trader journeys). Default 10,000 (well under a second); capped at 100,000 per tool call. Confidence intervals shrink roughly with the square root of paths.
  • avgWinR · number · requis
    Average winning trade in R-multiples, i.e. multiples of the amount risked per trade (1.5 = winners average 1.5x the risk).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • winRate · number · requis
    Probability a trade is a winner, as a FRACTION in [0, 1] (0.55 = 55% winners) - NOT percent units. The most impactful input: traders routinely overestimate it by a few points, which can flip EV negative, so prefer measured stats over self-reported ones.
  • winStdR · number · optionnel
    Standard deviation of winner sizes in R (0 = every winner is exactly avgWinR). Default 0. Adding spread makes streak damage more realistic.
  • avgLossR · number · optionnel
    Average losing trade in R, as a POSITIVE number. Default 1 (losers lose exactly the risked amount, i.e. stops are honored). Raise above 1 to model slippage or blown stops.
  • lossStdR · number · optionnel
    Standard deviation of loser sizes in R (0 = every loser is exactly avgLossR). Default 0.
  • riskMode · string · optionnel · percent-of-balance | percent-of-initial | fixed-amount
    How riskValue is interpreted. 'percent-of-balance' (default): risk compounds with the current balance. 'percent-of-initial': constant currency risk derived from the initial account size - how most prop traders size, since loss limits are fixed in currency. 'fixed-amount': explicit currency risked per 1R.
  • riskValue · number · requis
    Risk per trade - the value of 1R. PERCENT UNITS for percent modes (0.5 = 0.5% risked per trade; a typical prop range is 0.25-2), or a currency amount for 'fixed-amount'. NOT a fraction.
  • attemptCap · integer · optionnel
    Maximum challenge attempts per path before that path gives up. Default 25. Journey statistics (expected attempts/cost, P(funded)) are censored at this cap.
  • challenges · array · requis
    The challenges to simulate this trader across (1-12 entries; 2+ for a meaningful comparison). Mix dataset references and inline specs freely.
  • tradesPerDay · number · requis
    Average trades per simulated trading day. More trades per day means more ways to hit the daily loss limit within a single day.
  • simulateFunded · boolean · optionnel
    Whether to simulate the funded stage (payouts, blowup risk) after passing. Default true - EV is only meaningful with it on; set false to study the evaluation alone.
  • fundedHorizonDays · integer · optionnel
    Funded-stage horizon in trading days for the payout/EV simulation. Default 90 (about 4 calendar months). EV scales with this choice - state it when reporting EV.
  • tradesPerDayModel · string · optionnel · fixed | poisson
    'fixed' (default): the same count every day. 'poisson': daily count drawn Poisson(tradesPerDay); days can then have zero trades, which do not count as trading days.

  Exemple d'appel

  {"name": "propfirms_compare", "arguments": {"avgWinR": 1, "context": "texte", "winRate": 1, "riskValue": 1, "challenges": [], "tradesPerDay": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_get≈ 416 tokens

  One prop firm's full dossier by slug: general profile (platforms, markets, payments, Trustpilot, restricted countries), every challenge with its rules, live offers with promo codes and affiliate links, and the written overview (about, rules, payout policy, FAQ). Find slugs with propfirms_search. Uncaptured (null) fields are omitted; challenges reference applicable offers via offerIds into the firm-level offers list. For simulated pass odds on this firm's challenges (reference archetypes, same engine as luxalgo.com/prop-firms), use propfirms_pass_rates.

  Paramètres, retour & exemple (2)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • propfirmId · string · requis
    Public firm slug, e.g. 'ftmo'

  Exemple d'appel

  {"name": "propfirms_get", "arguments": {"context": "texte", "propfirmId": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_list_simulatable≈ 684 tokens

  List the prop firms in the live LuxAlgo directory together with every simulatable challenge (challengeId, display name, account size, currency, price, and its rule-semantics provenance). Call this first to discover the firmId + challengeId pairs accepted by propfirms_challenge_rules, propfirms_simulate, propfirms_optimal_risk, propfirms_compare and propfirms_simulate_trades. Challenges whose loss-rule semantics cannot be established are listed under notSimulatable instead of being guessed. The listing is data, not endorsement: firms are alphabetical - no recommendation or ranking is implied, and none should be presented. DATA SOURCE & PROVENANCE: firm data comes live from LuxAlgo's public, keyless prop-firm directory API - the data behind luxalgo.com/prop-firms. Rule semantics are used verbatim where the directory serves structured rule columns; where it serves only free text, semantics are inferred ONLY when one reasonable reading exists, and every inferred field is disclosed in `inferredFields` (provenance 'directory+inferred') - relay those to the user next to any numbers. Challenges whose loss rules cannot be established are refused as not simulatable rather than guessed. Firms change rules; each firm's own page is always authoritative. NOTE: this lists only the firms and challenges whose rules the engine can encode honestly. The full directory — every visible firm with platforms, prices, payout terms, and live offers/promo codes — is served by propfirms_search, propfirms_search_challenges, and propfirms_search_offers.

  Paramètres, retour & exemple (2)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • productType · string · optionnel · futures | cfd
    Optional filter to one instrument class. Omit to list every firm.

  Exemple d'appel

  {"name": "propfirms_list_simulatable", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_optimal_risk≈ 6838 tokens

  Sweep risk-per-trade over a grid, run the full journey simulation at every point, and report two optima separately: bestByPassProbability (the risk that maximizes a single attempt's chance of passing) and bestByEv (the risk that maximizes expected value across attempts, fees and funded payouts). They usually differ (diverges=true) - and that divergence is the insight: lower risk survives loss limits more often, but EV also weighs the cost of extra attempts and the size of funded payouts, which can favor a different risk. Never present one number as THE optimal risk; report both optima and the trade-off, and let the user choose. The sweep uses common random numbers (the same seed at every grid point), so curves are smooth and the argmax is signal, not Monte Carlo noise. Grid units follow riskMode: percent units for percent modes (default grid 0.1 to 3 in steps of 0.1, i.e. 0.1%-3% per trade), currency per trade for 'fixed-amount' (set min/max/step explicitly). Parametric trader only (riskValue is not a parameter here - the grid supplies it). Cost scales with grid size: one full simulation per point, so ~30 points at the default 10,000 paths takes roughly 10 seconds; use fewer paths or a coarser grid for a first pass, then refine around the optima. UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises. Results describe simulated outcomes of the user's own inputs under stated assumptions; they are not financial advice or a recommendation of any risk level.

  Paramètres, retour & exemple (20)

  Paramètres

  • max · number · optionnel
    Grid end, same units as min. Default 3 (= 3% per trade for percent modes).
  • min · number · optionnel
    Grid start, in the risk units of riskMode (percent units for percent modes, currency for 'fixed-amount'). Default 0.1 (= 0.1% per trade for percent modes).
  • seed · ? · optionnel
    RNG seed (integer or string). Default 42. Same inputs + seed reproduce byte-identical results - include the seed when reporting so users can reproduce the numbers.
  • spec · object · optionnel
    Inline challenge ruleset, for challenges not in the directory or for what-if rule edits. Mutually exclusive with firmId/challengeId. Identify the challenge EITHER by directory reference (firmId + challengeId, discovered via propfirms_list_simulatable; firmId accepts the directory id or the firm's name) OR by a full inline `spec` object - the exact shape propfirms_challenge_rules returns, so you can fetch a directory entry, change one rule, and re-simulate to model rule variations. Provide exactly one of the two forms; providing both or neither is an error. Directory references need network access; inline specs are fully offline.
  • step · number · optionnel
    Grid step, same units. Default 0.1. The sweep runs one full simulation per grid point, so (max - min) / step + 1 simulations in total - keep the grid coarse or paths low for a first pass.
  • paths · integer · optionnel
    Monte Carlo paths (independent simulated trader journeys). Default 10,000 (well under a second); capped at 100,000 per tool call. Confidence intervals shrink roughly with the square root of paths.
  • firmId · string · optionnel
    Directory firm id or firm name (e.g. 'ftmo' or 'FTMO'); discover with propfirms_list_simulatable. Must be paired with challengeId. Mutually exclusive with `spec`.
  • avgWinR · number · requis
    Average winning trade in R-multiples, i.e. multiples of the amount risked per trade (1.5 = winners average 1.5x the risk).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • winRate · number · requis
    Probability a trade is a winner, as a FRACTION in [0, 1] (0.55 = 55% winners) - NOT percent units. The most impactful input: traders routinely overestimate it by a few points, which can flip EV negative, so prefer measured stats over self-reported ones.
  • winStdR · number · optionnel
    Standard deviation of winner sizes in R (0 = every winner is exactly avgWinR). Default 0. Adding spread makes streak damage more realistic.
  • avgLossR · number · optionnel
    Average losing trade in R, as a POSITIVE number. Default 1 (losers lose exactly the risked amount, i.e. stops are honored). Raise above 1 to model slippage or blown stops.
  • lossStdR · number · optionnel
    Standard deviation of loser sizes in R (0 = every loser is exactly avgLossR). Default 0.
  • riskMode · string · optionnel · percent-of-balance | percent-of-initial | fixed-amount
    How riskValue is interpreted. 'percent-of-balance' (default): risk compounds with the current balance. 'percent-of-initial': constant currency risk derived from the initial account size - how most prop traders size, since loss limits are fixed in currency. 'fixed-amount': explicit currency risked per 1R.
  • attemptCap · integer · optionnel
    Maximum challenge attempts per path before that path gives up. Default 25. Journey statistics (expected attempts/cost, P(funded)) are censored at this cap.
  • challengeId · string · optionnel
    Directory challenge id; discover with propfirms_list_simulatable. Must be paired with firmId. Mutually exclusive with `spec`.
  • tradesPerDay · number · requis
    Average trades per simulated trading day. More trades per day means more ways to hit the daily loss limit within a single day.
  • simulateFunded · boolean · optionnel
    Whether to simulate the funded stage (payouts, blowup risk) after passing. Default true - EV is only meaningful with it on; set false to study the evaluation alone.
  • fundedHorizonDays · integer · optionnel
    Funded-stage horizon in trading days for the payout/EV simulation. Default 90 (about 4 calendar months). EV scales with this choice - state it when reporting EV.
  • tradesPerDayModel · string · optionnel · fixed | poisson
    'fixed' (default): the same count every day. 'poisson': daily count drawn Poisson(tradesPerDay); days can then have zero trades, which do not count as trading days.

  Exemple d'appel

  {"name": "propfirms_optimal_risk", "arguments": {"avgWinR": 1, "context": "texte", "winRate": 1, "tradesPerDay": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_pass_rates≈ 618 tokens

  Reference challenge pass rates computed live from the directory's encoded rules with the same engine, seed (42), path count (10,000) and reference archetypes luxalgo.com/prop-firms uses — per challenge and per archetype (developing 45% win rate / consistent 48% / proven edge 52%, all risking conservatively). Returns per-attempt pass probability with 95% CI, P(funded), expected attempts and total cost, EV, payout probability, funded-blowup probability, each cell's assumption flag ids, and the ruleset's provenance (structured directory columns vs fields inferred from listing text — always relay inferred fields). Deterministic per ruleset and cached — cheap to call. These are REFERENCE odds for orientation and comparison, not the user's personal odds: for their own statistics use propfirms_simulate (summary stats) or propfirms_simulate_trades (their real trade series). Not a ranking; a firm's page is authoritative for current rules (check lastVerified). Expected costs use the directory's listed challenge prices; full firm profiles and live offers are directory data (propfirms_get, propfirms_search_offers).

  Paramètres, retour & exemple (3)

  Paramètres

  • firmId · string · requis
    Directory firm id (propfirmId, e.g. 'ftmo') or firm name — from propfirms_list_simulatable.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • challengeId · string · optionnel
    One challenge id. Omit to compute every simulatable challenge the firm has.

  Exemple d'appel

  {"name": "propfirms_pass_rates", "arguments": {"firmId": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_search≈ 2062 tokens

  Search LuxAlgo's prop-firm catalog (proprietary trading firms offering funded accounts). Combine firm filters (platforms, markets, payment/payout methods, country availability, Trustpilot, year founded) with nested challenge filters (account size, price, steps, profit split, trading rules) and offer filters — a firm matches when at least one of its challenges/offers matches all of them. Omit every filter to list all firms. Use include to nest the matching challenges, live offers, and the written overview; for one firm's full dossier prefer propfirms_get. Uncaptured (null) fields are omitted from results; nested challenges reference offers via offerIds into the firm-level offers list. This tool returns directory data (what exists and on what terms), not outcomes: for simulated pass odds on a challenge found here, use propfirms_pass_rates or propfirms_simulate with its firm and challenge ids.

  Paramètres, retour & exemple (54)

  Paramètres

  • sort · string · optionnel · name | yearFounded | reviewsTrustPilotScore | reviewsTrustPilotCount
    Sort key (default name)
  • text · string · optionnel
    Case-insensitive search over firm name and slug, e.g. 'ftmo'
  • steps · integer · optionnel
    Exact evaluation step count (1 = instant/funded, 2 = two-step, …)
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • include · array · optionnel
    Extra payloads to nest on each firm (only children matching the filters are returned)
  • offerId · array · optionnel
    Public offer ids
  • currency · array · optionnel
    Account currencies, e.g. ['usd', 'eur']
  • interval · array · optionnel
    Challenge fee intervals, e.g. 'one-time', 'monthly'
  • priceMax · number · optionnel
    Maximum challenge fee (inclusive)
  • priceMin · number · optionnel
    Minimum challenge fee (inclusive)
  • stepsMax · integer · optionnel
    Maximum step count (ignored when steps is set)
  • stepsMin · integer · optionnel
    Minimum step count (ignored when steps is set)
  • direction · string · optionnel · asc | desc
    Sort direction; each sort key has a sensible default
  • offerText · string · optionnel
    Case-insensitive search over promo code and offer descriptions
  • pageIndex · integer · optionnel
    0-based page index (default 0)
  • promoCode · string · optionnel
    Case-insensitive substring of the promo code
  • isFeatured · boolean · optionnel
    Only featured offers when true
  • maxLossMax · number · optionnel
    Upper bound on the overall-loss limit magnitude
  • propfirmId · array · optionnel
    Public firm slugs, e.g. ['ftmo']
  • autoTrading · boolean · optionnel
    Whether automated trading (EAs/bots) is allowed
  • availableIn · array · optionnel
    Country names the firm must NOT restrict, e.g. ['United States']
  • challengeId · array · optionnel
    Public challenge ids
  • copyTrading · boolean · optionnel
    Whether copy trading is allowed
  • countryIso2 · array · optionnel
    ISO-2 headquarters countries, e.g. ['GB', 'US']
  • discountMax · number · optionnel
    Maximum discount value
  • discountMin · number · optionnel
    Minimum discount value
  • maxLossMode · array · optionnel
    Drawdown modes; challenges without a captured mode never match
  • newsTrading · boolean · optionnel
    Whether news trading is allowed
  • dailyLossMax · number · optionnel
    Upper bound on the daily-loss limit magnitude (smaller = stricter)
  • pageQuantity · integer · optionnel
    Page size (default 50, max 100)
  • productTypes · array · optionnel
    Product types the firm must offer at least one of, e.g. 'CFD', 'Futures'
  • challengeName · string · optionnel
    Case-insensitive substring of the challenge name
  • payoutMethods · array · optionnel
    Payout methods the firm must offer at least one of, e.g. 'Bank Transfer', 'Crypto'
  • accountSizeMax · number · optionnel
    Maximum account size (inclusive)
  • accountSizeMin · number · optionnel
    Minimum account size (inclusive)
  • hasActiveOffer · boolean · optionnel
    When true, the firm must currently have a live (active, unexpired) offer
  • includeExpired · boolean · optionnel
    When true, ended offers are not hidden (default false)
  • maxLeverageMin · number · optionnel
    Minimum max leverage
  • maxYearFounded · integer · optionnel
    Inclusive maximum year founded
  • minYearFounded · integer · optionnel
    Inclusive minimum year founded
  • paymentMethods · array · optionnel
    Payment methods the firm must accept at least one of, e.g. 'Crypto', 'PayPal'
  • profitSplitMin · number · optionnel
    Minimum trader profit-split percent
  • weekendHolding · boolean · optionnel
    Whether holding over the weekend is allowed
  • includeInactive · boolean · optionnel
    When true, inactive offers are not hidden (default false)
  • isFeeRefundable · boolean · optionnel
    Whether the challenge fee is refundable
  • overnightHolding · boolean · optionnel
    Whether holding overnight is allowed
  • stoplossRequired · boolean · optionnel
    Whether a stop loss is required
  • tradingPlatforms · array · optionnel
    Platforms the firm must offer at least one of, e.g. 'MT5', 'cTrader', 'TradingView'
  • discountIsPercent · boolean · optionnel
    true for percent discounts, false for absolute amounts
  • minTradingDaysMax · number · optionnel
    Maximum required minimum trading days (finds less-strict challenges)
  • tradedMarketTypes · array · optionnel
    Markets the firm must offer at least one of, e.g. 'forex', 'indices', 'commodities'
  • isPreferredPartner · boolean · optionnel
    Only LuxAlgo preferred-partner firms when true
  • minTrustPilotCount · number · optionnel
    Minimum Trustpilot review count
  • minTrustPilotScore · number · optionnel
    Minimum Trustpilot score

  Exemple d'appel

  {"name": "propfirms_search", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_search_challenges≈ 1522 tokens

  Search funded-account challenges across all visible prop firms. Filter by challenge rules (account size, fee, steps, profit split, drawdown mode, news/copy/auto trading, weekend holding, …) and by parent-firm properties. Pass propfirmId to list one firm's challenges, or challengeId to fetch specific ones. include=['offers'] returns a deduplicated top-level offers list, with each challenge referencing its applicable offers via offerIds (firm-wide offers included). Uncaptured (null) rule fields are omitted from results and never match filters. This returns each challenge's listed rules and terms, not outcomes: to simulate a challenge found here pass its ids to propfirms_simulate or propfirms_pass_rates, and to screen one strategy across many challenges at once use propfirms_validate_strategy.

  Paramètres, retour & exemple (36)

  Paramètres

  • sort · string · optionnel · challengeName | accountSize | price | steps | profitSplitPercent
    Sort key (default accountSize descending)
  • text · string · optionnel
    Case-insensitive search over challenge name and firm name/slug
  • steps · integer · optionnel
    Exact evaluation step count (1 = instant/funded, 2 = two-step, …)
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • include · array · optionnel
    Pass ['offers'] to attach live offers that apply to each challenge
  • interval · array · optionnel
    Challenge fee intervals, e.g. 'one-time', 'monthly'
  • priceMax · number · optionnel
    Maximum challenge fee (inclusive)
  • priceMin · number · optionnel
    Minimum challenge fee (inclusive)
  • stepsMax · integer · optionnel
    Maximum step count (ignored when steps is set)
  • stepsMin · integer · optionnel
    Minimum step count (ignored when steps is set)
  • direction · string · optionnel · asc | desc
    Sort direction; each sort key has a sensible default
  • pageIndex · integer · optionnel
    0-based page index (default 0)
  • maxLossMax · number · optionnel
    Upper bound on the overall-loss limit magnitude
  • propfirmId · array · optionnel
    Public firm slugs, e.g. ['ftmo']
  • autoTrading · boolean · optionnel
    Whether automated trading (EAs/bots) is allowed
  • availableIn · array · optionnel
    Country names the firm must NOT restrict, e.g. ['United States']
  • challengeId · array · optionnel
    Public challenge ids
  • copyTrading · boolean · optionnel
    Whether copy trading is allowed
  • maxLossMode · array · optionnel
    Drawdown modes; challenges without a captured mode never match
  • newsTrading · boolean · optionnel
    Whether news trading is allowed
  • dailyLossMax · number · optionnel
    Upper bound on the daily-loss limit magnitude (smaller = stricter)
  • pageQuantity · integer · optionnel
    Page size (default 50, max 100)
  • productTypes · array · optionnel
    Product types the firm must offer at least one of, e.g. 'CFD', 'Futures'
  • challengeName · string · optionnel
    Case-insensitive substring of the challenge name
  • accountSizeMax · number · optionnel
    Maximum account size (inclusive)
  • accountSizeMin · number · optionnel
    Minimum account size (inclusive)
  • maxLeverageMin · number · optionnel
    Minimum max leverage
  • profitSplitMin · number · optionnel
    Minimum trader profit-split percent
  • weekendHolding · boolean · optionnel
    Whether holding over the weekend is allowed
  • isFeeRefundable · boolean · optionnel
    Whether the challenge fee is refundable
  • overnightHolding · boolean · optionnel
    Whether holding overnight is allowed
  • stoplossRequired · boolean · optionnel
    Whether a stop loss is required
  • tradingPlatforms · array · optionnel
    Platforms the firm must offer at least one of, e.g. 'MT5', 'cTrader', 'TradingView'
  • minTradingDaysMax · number · optionnel
    Maximum required minimum trading days (finds less-strict challenges)
  • tradedMarketTypes · array · optionnel
    Markets the firm must offer at least one of, e.g. 'forex', 'indices', 'commodities'
  • isPreferredPartner · boolean · optionnel
    Only LuxAlgo preferred-partner firms when true

  Exemple d'appel

  {"name": "propfirms_search_challenges", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_search_offers≈ 824 tokens

  Search promotional offers (discounts and promo codes) across prop firms — defaults to live (active, unexpired) offers only. propfirmId narrows to one firm; challengeId resolves the offers that apply to a challenge (firm-wide offers included). Every offer carries the promo code, discount, end date, and affiliate link.

  Paramètres, retour & exemple (18)

  Paramètres

  • sort · string · optionnel · discountValue | endsAt | promoCode
    Sort key (default: featured first, then discount)
  • text · string · optionnel
    Case-insensitive search over promo code, descriptions, and firm name/slug
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • offerId · array · optionnel
    Public offer ids
  • isActive · boolean · optionnel
    Defaults to live offers only; pass false to look at inactive offers
  • direction · string · optionnel · asc | desc
    Sort direction; each sort key has a sensible default
  • offerText · string · optionnel
    Case-insensitive search over promo code and offer descriptions
  • pageIndex · integer · optionnel
    0-based page index (default 0)
  • promoCode · string · optionnel
    Case-insensitive substring of the promo code
  • isFeatured · boolean · optionnel
    Only featured offers when true
  • propfirmId · array · optionnel
    Public firm slugs, e.g. ['ftmo']
  • challengeId · array · optionnel
    Public challenge ids; an offer matches when it applies to at least one (all-challenges offers match that firm's challenges)
  • discountMax · number · optionnel
    Maximum discount value
  • discountMin · number · optionnel
    Minimum discount value
  • pageQuantity · integer · optionnel
    Page size (default 50, max 100)
  • includeExpired · boolean · optionnel
    When true, ended offers are not hidden (default false)
  • includeInactive · boolean · optionnel
    When true, inactive offers are not hidden (default false)
  • discountIsPercent · boolean · optionnel
    true for percent discounts, false for absolute amounts

  Exemple d'appel

  {"name": "propfirms_search_offers", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_simulate≈ 7400 tokens

  Monte Carlo-simulate a trader with the given statistics through a prop-firm challenge and (by default) a funded horizon. Answers: "What is my chance of passing per attempt, and of ever getting funded? How many attempts and how much total money should I expect? Is this challenge positive expected value for me, and which rule actually kills my attempts?" Identify the challenge EITHER by directory reference (firmId + challengeId, discovered via propfirms_list_simulatable; firmId accepts the directory id or the firm's name) OR by a full inline `spec` object - the exact shape propfirms_challenge_rules returns, so you can fetch a directory entry, change one rule, and re-simulate to model rule variations. Provide exactly one of the two forms; providing both or neither is an error. Directory references need network access; inline specs are fully offline. The trader is described by flattened parametric fields (one clean design used across all tools): winRate (a FRACTION 0-1), avgWinR/avgLossR and optional winStdR/lossStdR in R-multiples (sizes relative to the amount risked per trade), tradesPerDay with a 'fixed' or 'poisson' day model, and risk sizing via riskMode + riskValue (percent units for percent modes). If you have the user's raw trade series rather than summary stats, prefer propfirms_simulate_trades - it preserves streaks. Returns structuredContent with the full SimResult: perAttempt.passProbability with a Wilson 95% CI and per-step pass rates plus a failure breakdown by rule (daily-loss vs max-loss vs time-limit - which tells the user WHAT to fix); journey.fundedProbability, attempts and cost distributions (cost includes prices, resets, monthly billing, activation, minus refunds), costGivenFunded and daysToFunded; perAttempt.avgDaysWhenPassed/avgDaysWhenFailed and perAttempt.stagnationDays (the longest run of days without a new equity high per attempt - the dead time between progress, which grows sharply as risk per trade shrinks); funded-stage payout distributions plus funded.payoutProbability (P(at least one payout | funded)) and funded.daysToFirstPayout - with payout gating these can be the deciding numbers, since getting funded is not the same as getting paid; ev.evTotal (mean payouts minus costs) with evStandardError and pPositive; drawdown stats; and assumptions (the fully-resolved spec/profile/options the engine actually ran, plus flags and disclaimer). Histogram arrays are omitted unless includeHistograms=true. A compact human summary is returned as text alongside. SIMULATED RULES (engine v1): consistency rules (steps[].consistency) and funded payout gating (funded.payoutRules) are actually SIMULATED, not merely flagged. Consistency uses a rational stop rule (the trader stops a day once more profit cannot help and keeps trading until the best-day share complies - flag 'consistency-stop-rule'); payouts follow a maximum-withdrawal model (withdraw everything the rules allow above buffer/caps, never below the loss floor; balances and floors carry across payouts - flag 'funded-withdrawal-model'); a funded consistency gate is checked per payout window (flag 'funded-consistency-window-approximated'). UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises. DATA SOURCE & PROVENANCE: firm data comes live from LuxAlgo's public, keyless prop-firm directory API - the data behind luxalgo.com/prop-firms. Rule semantics are used verbatim where the directory serves structured rule columns; where it serves only free text, semantics are inferred ONLY when one reasonable reading exists, and every inferred field is disclosed in `inferredFields` (provenance 'directory+inferred') - relay those to the user next to any numbers. Challenges whose loss rules cannot be established are refused as not simulatable rather than guessed. Firms change rules; each firm's own page is always authoritative.

  Paramètres, retour & exemple (19)

  Paramètres

  • seed · ? · optionnel
    RNG seed (integer or string). Default 42. Same inputs + seed reproduce byte-identical results - include the seed when reporting so users can reproduce the numbers.
  • spec · object · optionnel
    Inline challenge ruleset, for challenges not in the directory or for what-if rule edits. Mutually exclusive with firmId/challengeId. Identify the challenge EITHER by directory reference (firmId + challengeId, discovered via propfirms_list_simulatable; firmId accepts the directory id or the firm's name) OR by a full inline `spec` object - the exact shape propfirms_challenge_rules returns, so you can fetch a directory entry, change one rule, and re-simulate to model rule variations. Provide exactly one of the two forms; providing both or neither is an error. Directory references need network access; inline specs are fully offline.
  • paths · integer · optionnel
    Monte Carlo paths (independent simulated trader journeys). Default 10,000 (well under a second); capped at 100,000 per tool call. Confidence intervals shrink roughly with the square root of paths.
  • firmId · string · optionnel
    Directory firm id or firm name (e.g. 'ftmo' or 'FTMO'); discover with propfirms_list_simulatable. Must be paired with challengeId. Mutually exclusive with `spec`.
  • avgWinR · number · requis
    Average winning trade in R-multiples, i.e. multiples of the amount risked per trade (1.5 = winners average 1.5x the risk).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • winRate · number · requis
    Probability a trade is a winner, as a FRACTION in [0, 1] (0.55 = 55% winners) - NOT percent units. The most impactful input: traders routinely overestimate it by a few points, which can flip EV negative, so prefer measured stats over self-reported ones.
  • winStdR · number · optionnel
    Standard deviation of winner sizes in R (0 = every winner is exactly avgWinR). Default 0. Adding spread makes streak damage more realistic.
  • avgLossR · number · optionnel
    Average losing trade in R, as a POSITIVE number. Default 1 (losers lose exactly the risked amount, i.e. stops are honored). Raise above 1 to model slippage or blown stops.
  • lossStdR · number · optionnel
    Standard deviation of loser sizes in R (0 = every loser is exactly avgLossR). Default 0.
  • riskMode · string · optionnel · percent-of-balance | percent-of-initial | fixed-amount
    How riskValue is interpreted. 'percent-of-balance' (default): risk compounds with the current balance. 'percent-of-initial': constant currency risk derived from the initial account size - how most prop traders size, since loss limits are fixed in currency. 'fixed-amount': explicit currency risked per 1R.
  • riskValue · number · requis
    Risk per trade - the value of 1R. PERCENT UNITS for percent modes (0.5 = 0.5% risked per trade; a typical prop range is 0.25-2), or a currency amount for 'fixed-amount'. NOT a fraction.
  • attemptCap · integer · optionnel
    Maximum challenge attempts per path before that path gives up. Default 25. Journey statistics (expected attempts/cost, P(funded)) are censored at this cap.
  • challengeId · string · optionnel
    Directory challenge id; discover with propfirms_list_simulatable. Must be paired with firmId. Mutually exclusive with `spec`.
  • tradesPerDay · number · requis
    Average trades per simulated trading day. More trades per day means more ways to hit the daily loss limit within a single day.
  • simulateFunded · boolean · optionnel
    Whether to simulate the funded stage (payouts, blowup risk) after passing. Default true - EV is only meaningful with it on; set false to study the evaluation alone.
  • fundedHorizonDays · integer · optionnel
    Funded-stage horizon in trading days for the payout/EV simulation. Default 90 (about 4 calendar months). EV scales with this choice - state it when reporting EV.
  • includeHistograms · boolean · optionnel
    Include histogram arrays (attempts, cost, net, drawdown) in the result. Default FALSE for this tool to keep responses compact; summary quantiles (p05...p95) are always included.
  • tradesPerDayModel · string · optionnel · fixed | poisson
    'fixed' (default): the same count every day. 'poisson': daily count drawn Poisson(tradesPerDay); days can then have zero trades, which do not count as trading days.

  Exemple d'appel

  {"name": "propfirms_simulate", "arguments": {"avgWinR": 1, "context": "texte", "winRate": 1, "riskValue": 1, "tradesPerDay": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_simulate_trades≈ 8426 tokens

  Simulate a challenge by resampling the trader's OWN R-multiple trade series with a stationary block bootstrap instead of a win-rate model. Why resampling matters: challenge rules are breached by streaks, not by averages - a daily-loss limit dies to a cluster of losses inside one day, and a trailing drawdown dies to a losing streak right after an equity peak. Real trade series are streaky (autocorrelation, volatility clustering, edge that comes and goes), and the stationary bootstrap resamples contiguous blocks of the actual series (geometric length, mean blockMeanLength, default 5 trades), so the trader's real streak structure survives into every simulated day. A parametric model with identical summary statistics shuffles trades independently and therefore understates breach risk for streaky traders. Use propfirms_simulate when only summary stats are available; use this whenever the actual trades are. Provide the series as rSeries (array of R-multiples: each trade's P&L divided by the amount risked on it), rSeriesText (pasted JSON/CSV/whitespace text, optional 'R' suffix per value), or one of the timestamped-log inputs below; exactly one of the four, at least 10 trades, 100+ strongly recommended. Returns the same full SimResult as propfirms_simulate (structuredContent, histograms off by default) plus a text summary that also reports the sample's win rate and mean R. TIMESTAMPED LOGS: tradeLogText accepts a pasted CSV/TSV trade log with a header row (open time and R required; close time and direction optional; loose header names are matched; timestamps without an offset are read as UTC). The R-series and, unless tradesPerDay is passed, the trades-per-day rate are derived from the log, and parse warnings are surfaced in the text output. NEWS WINDOWS: with a timestamped input, newsFilter runs the simulation TWICE on the same seed and options, once on the full history and once without the trades opened inside configurable windows around scheduled releases (a built-in recurring-template calendar of high- and medium-impact events across USD, EUR, GBP, JPY, AUD, CAD, CHF, NZD, plus optional custom event times). The returned SimResult is the news-avoided scenario; structuredContent.newsComparison carries both scenarios' pass probability, funded probability and EV, the excluded-trade count, and a calendar caveat that must be relayed verbatim. PORTFOLIO MODE: tradeLogTexts (2 to 5 logs) merges several timestamped histories into one chronological series and simulates the combined account, so cross-strategy loss clustering survives. Overlap across the histories is ALWAYS analyzed and attached as structuredContent.portfolioOverlap; the text summary carries the audit-risk verdict, and a 'high' verdict is an explicit warning that a prop firm may audit or refuse payouts for correlated accounts. SIMULATED RULES (engine v1): consistency rules (steps[].consistency) and funded payout gating (funded.payoutRules) are actually SIMULATED, not merely flagged. Consistency uses a rational stop rule (the trader stops a day once more profit cannot help and keeps trading until the best-day share complies - flag 'consistency-stop-rule'); payouts follow a maximum-withdrawal model (withdraw everything the rules allow above buffer/caps, never below the loss floor; balances and floors carry across payouts - flag 'funded-withdrawal-model'); a funded consistency gate is checked per payout window (flag 'funded-consistency-window-approximated'). UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises.

  Paramètres, retour & exemple (21)

  Paramètres

  • seed · ? · optionnel
    RNG seed (integer or string). Default 42. Same inputs + seed reproduce byte-identical results - include the seed when reporting so users can reproduce the numbers.
  • spec · object · optionnel
    Inline challenge ruleset, for challenges not in the directory or for what-if rule edits. Mutually exclusive with firmId/challengeId. Identify the challenge EITHER by directory reference (firmId + challengeId, discovered via propfirms_list_simulatable; firmId accepts the directory id or the firm's name) OR by a full inline `spec` object - the exact shape propfirms_challenge_rules returns, so you can fetch a directory entry, change one rule, and re-simulate to model rule variations. Provide exactly one of the two forms; providing both or neither is an error. Directory references need network access; inline specs are fully offline.
  • paths · integer · optionnel
    Monte Carlo paths (independent simulated trader journeys). Default 10,000 (well under a second); capped at 100,000 per tool call. Confidence intervals shrink roughly with the square root of paths.
  • firmId · string · optionnel
    Directory firm id or firm name (e.g. 'ftmo' or 'FTMO'); discover with propfirms_list_simulatable. Must be paired with challengeId. Mutually exclusive with `spec`.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • rSeries · array · optionnel
    The trader's real trades as R-multiples in chronological order: each trade's P&L divided by the amount risked on it (+1.8 = won 1.8x risk, -1 = lost exactly the risk, -1.4 = stop slipped 40%). At least 10 trades; 100+ strongly recommended - short series make the simulation overconfident in the sample. Mutually exclusive with rSeriesText, tradeLogText, and tradeLogTexts.
  • riskMode · string · optionnel · percent-of-balance | percent-of-initial | fixed-amount
    How riskValue is interpreted. 'percent-of-balance' (default): risk compounds with the current balance. 'percent-of-initial': constant currency risk derived from the initial account size - how most prop traders size, since loss limits are fixed in currency. 'fixed-amount': explicit currency risked per 1R.
  • riskValue · number · requis
    Risk per trade - the value of 1R. PERCENT UNITS for percent modes (0.5 = 0.5% risked per trade; a typical prop range is 0.25-2), or a currency amount for 'fixed-amount'. NOT a fraction.
  • attemptCap · integer · optionnel
    Maximum challenge attempts per path before that path gives up. Default 25. Journey statistics (expected attempts/cost, P(funded)) are censored at this cap.
  • importRisk · string · optionnel
    Risk per trade for imports that carry P&L but no risk data (e.g. TradingView, MT5 deals, broker JSON, ThinkOrSwim): cash risked per trade ("25") or a percent of entry value ("1%"). Applies to tradeLogText/tradeLogTexts only, is labeled rSource inferred, and is never applied silently: without it such files are refused with needs-risk.
  • newsFilter · object · optionnel
    What-if comparison: what are my odds if I do not OPEN trades around scheduled news? Requires a timestamped input (tradeLogText or tradeLogTexts). The simulation runs TWICE with the same seed and options, once on the full history and once with every trade opened inside [event - preMinutes, event + postMinutes] removed; trades opened earlier but held through an event are only counted, not removed. The returned SimResult is the news-AVOIDED scenario; structuredContent.newsComparison carries both scenarios' headline numbers, the excluded-trade count, and a calendar caveat that MUST be relayed to the user (the calendar is a recurring-template approximation of scheduled releases, not a historical feed).
  • challengeId · string · optionnel
    Directory challenge id; discover with propfirms_list_simulatable. Must be paired with firmId. Mutually exclusive with `spec`.
  • rSeriesText · string · optionnel
    The same series as pasted text: a JSON array, CSV, or whitespace/newline separated numbers, with an optional 'R' suffix per value (e.g. "1.8R, -1R, 0.4, 2.1"). Parsed with the library's parseRSeries; unparseable tokens are reported back. Mutually exclusive with rSeries, tradeLogText, and tradeLogTexts.
  • tradeLogText · string · optionnel
    The trader's trades as one pasted TIMESTAMPED log instead of a bare series. Accepted formats, auto-detected: the generic CSV template (header: open time,close time,symbol,direction,quantity,entry price,exit price,stop loss,pnl,fees,r), plain timestamped CSV/TSV logs (open time + R columns), real platform exports: TradingView strategy-tester list of trades (both generations), MT4/MT5 account statements (CSV or pasted HTML), MT5 deals tables, and ThinkOrSwim account statements, plus broker trade-history JSON in the @luxalgo/broker-sdk shape (a bare fills array, {"trades": [...]}, or one snapshot account; fills replay FIFO into round trips with price-based P&L, disclosed). Timestamps WITHOUT an explicit offset are read as UTC. Files that carry P&L but no risk information need importRisk to become R-multiples; ambiguous rule readings are refused with diagnostics rather than guessed, and skipped rows are reported as warnings. Timestamps unlock two things a bare series cannot do: tradesPerDay is derived from the log when not given, and newsFilter can compare odds with and without trading around news. Mutually exclusive with rSeries, rSeriesText, and tradeLogTexts.
  • tradesPerDay · number · optionnel
    Average trades per simulated trading day. REQUIRED with rSeries/rSeriesText, which carry no timestamps. Optional with tradeLogText/tradeLogTexts: when omitted it is derived from the log's own timestamps (trades divided by distinct UTC trading days) and the output says so. More trades per day means more ways to hit the daily loss limit within a single day.
  • tradeLogTexts · array · optionnel
    PORTFOLIO MODE: 2 to 5 timestamped trade logs (same format as tradeLogText), one per strategy or account. They are merged into one chronological series and the combined account is simulated, which preserves cross-strategy loss clustering (exactly what daily and max loss limits punish). Overlap across the histories is ALWAYS analyzed and attached as structuredContent.portfolioOverlap with an audit-risk verdict; see the attached structuredContent.portfolioOverlap analysis for the methodology. Mutually exclusive with rSeries, rSeriesText, and tradeLogText.
  • simulateFunded · boolean · optionnel
    Whether to simulate the funded stage (payouts, blowup risk) after passing. Default true - EV is only meaningful with it on; set false to study the evaluation alone.
  • blockMeanLength · number · optionnel
    Mean block length of the stationary bootstrap (geometrically distributed blocks). Default 5 trades. 1 = i.i.d. resampling (destroys streaks - only for comparison); raise toward 10 if the trader's edge comes and goes in long regimes.
  • fundedHorizonDays · integer · optionnel
    Funded-stage horizon in trading days for the payout/EV simulation. Default 90 (about 4 calendar months). EV scales with this choice - state it when reporting EV.
  • includeHistograms · boolean · optionnel
    Include histogram arrays (attempts, cost, net, drawdown) in the result. Default FALSE for this tool to keep responses compact; summary quantiles (p05...p95) are always included.
  • tradesPerDayModel · string · optionnel · fixed | poisson
    'fixed' (default): the same count every day. 'poisson': daily count drawn Poisson(tradesPerDay); days can then have zero trades, which do not count as trading days.

  Exemple d'appel

  {"name": "propfirms_simulate_trades", "arguments": {"context": "texte", "riskValue": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• propfirms_validate_strategy≈ 2051 tokens

  Answer 'which challenges would MY strategy actually pass?' in one call: simulate the given strategy through every simulatable challenge in the live directory (optionally scoped by productType, account-size range, priceMax, or firm) and split the results by an explicit, caller-stated bar. Describe the strategy EITHER as real trades (rSeries/rSeriesText R-multiples, preferred: the stationary block bootstrap preserves streaks, which is what breaches loss limits) OR as summary stats (winRate + avgWinR, optional spreads), plus tradesPerDay and risk sizing (riskMode + riskValue). The bar is minPassPerAttempt (a fraction, default 0.5) with optional requirePositiveEv; always state the bar when relaying results. Returns per challenge: pass probability per attempt with 95% CI, P(funded), expected attempts and total cost, EV over the funded horizon, P(EV>0), assumption flag ids, and which rule semantics were inferred from listing text. HONESTY FRAME: this is a screen of distributions for the caller's inputs and bar, NOT a ranking or endorsement; challenges whose rules cannot be encoded honestly are excluded and counted, never guessed; flagged (unsimulated) rules make numbers optimistic, so relay flags. One full simulation runs per challenge (default 5,000 paths each; results are deterministic per seed), and scopes above 40 challenges are refused rather than silently truncated: narrow the scope instead. Numbers move with risk sizing; sweep one challenge with propfirms_optimal_risk afterwards. Fees and expected costs use the directory's listed prices (live discounts are NOT applied); prices, firm profiles, and current offers are directory data (propfirms_search_challenges, propfirms_get, propfirms_search_offers).

  Paramètres, retour & exemple (25)

  Paramètres

  • firm · string · optionnel
    Restrict to one firm by propfirmId or name (e.g. 'ftmo').
  • seed · ? · optionnel
    RNG seed (integer or string). Default 42. Same inputs + seed reproduce byte-identical results — include the seed when reporting so users can reproduce the numbers.
  • paths · integer · optionnel
    Monte Carlo paths PER CHALLENGE. Default 5,000 here (one full simulation runs per challenge in scope, so this tool costs number-of-challenges times one simulation); raise it to tighten confidence intervals on a narrowed scope.
  • avgWinR · number · optionnel
    Average winning trade in R-multiples, i.e. multiples of the amount risked per trade (1.5 = winners average 1.5x the risk).
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • rSeries · array · optionnel
    The strategy's real trades as R-multiples in chronological order (P&L divided by amount risked; +1.8 = won 1.8x risk, -1 = lost the risk). At least 10 trades, 100+ recommended. When given, the screen uses the stationary block bootstrap (streaks preserved) instead of winRate/avgWinR.
  • winRate · number · optionnel
    Probability a trade is a winner, as a FRACTION in [0, 1] (0.55 = 55% winners) — NOT percent units. The most impactful input: traders routinely overestimate it by a few points, which can flip EV negative, so prefer measured stats over self-reported ones.
  • winStdR · number · optionnel
    Standard deviation of winner sizes in R (0 = every winner is exactly avgWinR). Default 0. Adding spread makes streak damage more realistic.
  • avgLossR · number · optionnel
    Average losing trade in R, as a POSITIVE number. Default 1 (losers lose exactly the risked amount, i.e. stops are honored). Raise above 1 to model slippage or blown stops.
  • lossStdR · number · optionnel
    Standard deviation of loser sizes in R (0 = every loser is exactly avgLossR). Default 0.
  • priceMax · number · optionnel
    Only challenges costing at most this.
  • riskMode · string · optionnel · percent-of-balance | percent-of-initial | fixed-amount
    How riskValue is interpreted. 'percent-of-balance' (default): risk compounds with the current balance. 'percent-of-initial': constant currency risk derived from the initial account size — how most prop traders size, since loss limits are fixed in currency. 'fixed-amount': explicit currency risked per 1R.
  • riskValue · number · requis
    Risk per trade — the value of 1R. PERCENT UNITS for percent modes (0.5 = 0.5% risked per trade; a typical prop range is 0.25-2), or a currency amount for 'fixed-amount'. NOT a fraction.
  • attemptCap · integer · optionnel
    Maximum challenge attempts per path before that path gives up. Default 25. Journey statistics (expected attempts/cost, P(funded)) are censored at this cap.
  • productType · string · optionnel · futures | cfd
    Restrict the screen to one instrument class.
  • rSeriesText · string · optionnel
    The same series as pasted text (JSON, CSV, or whitespace separated, optional 'R' suffix). Mutually exclusive with rSeries.
  • tradesPerDay · number · requis
    Average trades per simulated trading day. More trades per day means more ways to hit the daily loss limit within a single day.
  • accountSizeMax · number · optionnel
    Only challenges with at most this account size.
  • accountSizeMin · number · optionnel
    Only challenges with at least this account size.
  • simulateFunded · boolean · optionnel
    Whether to simulate the funded stage (payouts, blowup risk) after passing. Default true — EV is only meaningful with it on; set false to study the evaluation alone.
  • blockMeanLength · number · optionnel
    Bootstrap mean block length in trades. Default 5. Only used with rSeries/rSeriesText.
  • fundedHorizonDays · integer · optionnel
    Funded-stage horizon in trading days for the payout/EV simulation. Default 90 (about 4 calendar months). EV scales with this choice — state it when reporting EV.
  • minPassPerAttempt · number · optionnel
    The pass bar as a FRACTION in [0, 1]: a challenge counts as passing when the simulated per-attempt pass probability is at least this. Default 0.5. State the bar when relaying results.
  • requirePositiveEv · boolean · optionnel
    Additionally require expected value (payouts minus all fees over the funded horizon) above zero. Default false.
  • tradesPerDayModel · string · optionnel · fixed | poisson
    'fixed' (default): the same count every day. 'poisson': daily count drawn Poisson(tradesPerDay); days can then have zero trades, which do not count as trading days.

  Exemple d'appel

  {"name": "propfirms_validate_strategy", "arguments": {"context": "texte", "riskValue": 1, "tradesPerDay": 1}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• trackers_datasets≈ 560 tokens

  The Market Trackers catalog: every dataset of US public-record market data the LuxAlgo pipeline publishes as CC0 dumps — congressional trades, insider (Forms 3/4/5) transactions, 13F holdings, federal contracts and grants, lobbying filings, FINRA short-sale volume, granted patents, clinical trials, FDA drug events, CFTC positioning, federal bills, FEC campaign finance, hearing transcripts, Federal Reserve communications, committee assignments, Wikipedia pageviews. Returns each dataset's row count, freshness, the years with data (live tree vs deep-history archives), and whether it is ticker-searchable. Pass dataset for the full field roster, filterable paths, caveats, per-year coverage, source health, and dump URLs — read it before composing trackers_query filters.

  Paramètres, retour & exemple (2)

  Paramètres

  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • dataset · string · optionnel · congress-trades | insider-transactions | thirteenf-holdings | gov-contracts | gov-grants | lobbying-filings | short-volume | committee-assignments
    One dataset for the detailed view; omit to list all

  Exemple d'appel

  {"name": "trackers_datasets", "arguments": {"context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• trackers_latest≈ 756 tokens

  What the last daily publish added to one dataset — the newest ingestion day's rows (the dumps' latest.json), optionally narrowed by ticker or text. The cheapest way to see what is new: today's insider filings, this week's congressional disclosures, the latest lobbying registrations. Not available for snapshot-only bulk datasets (patents); use trackers_query there.

  Paramètres, retour & exemple (8)

  Paramètres

  • sort · string · optionnel · newest | oldest
    Order by event date (default newest)
  • text · string · optionnel
    Case-insensitive substring over the dataset's name/title fields (member, insider, issuer, recipient, registrant and client, sponsor, assignee, bill title, …); see textPaths in trackers_datasets
  • limit · integer · optionnel
    Rows to return (default 25, max 100)
  • where · object · optionnel
    Exact field matches by dot path, e.g. {"side":"buy"}, {"member.state":"CA"}, {"code":"P"}, {"formType":"4"}; string comparisons are case-insensitive, arrays match when any element does
  • offset · integer · optionnel
    Rows to skip, for paging (default 0)
  • ticker · string · optionnel
    Trading symbol, case-insensitive (e.g. 'NVDA'); matches the dataset's ticker field(s). Only datasets flagged tickerSearchable carry tickers.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • dataset · string · requis · congress-trades | insider-transactions | thirteenf-holdings | gov-contracts | gov-grants | lobbying-filings | short-volume | committee-assignments
    Dataset id, from trackers_datasets

  Exemple d'appel

  {"name": "trackers_latest", "arguments": {"context": "texte", "dataset": "congress-trades"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• trackers_query≈ 1004 tokens

  Search one Market Trackers dataset by ticker, free text, exact field values, and event-date range, with paging and newest/oldest ordering. Data is read from year-sharded CC0 dumps: pass years (or since/until) to choose which years to read — default is the newest year with data. Deep-history years (see archiveYears in trackers_datasets) can be tens of MB compressed each, so read them one or two at a time; the tool refuses selections over its byte budget and says how to narrow. Every row carries provenance.sourceUrl (the SEC filing, disclosure, award, or record it came from). Examples: insider purchases at NVDA in 2024 → dataset insider-transactions, ticker NVDA, years [2024], where {code: 'P'}; a member of Congress's trades → congress-trades, text set to their name; who lobbied on a bill → lobbying-filings, text 'H.R.1234'.

  Paramètres, retour & exemple (11)

  Paramètres

  • sort · string · optionnel · newest | oldest
    Order by event date (default newest)
  • text · string · optionnel
    Case-insensitive substring over the dataset's name/title fields (member, insider, issuer, recipient, registrant and client, sponsor, assignee, bill title, …); see textPaths in trackers_datasets
  • limit · integer · optionnel
    Rows to return (default 25, max 100)
  • since · string · optionnel
    Earliest event date (YYYY-MM-DD, YYYY-MM or YYYY), inclusive
  • until · string · optionnel
    Latest event date, inclusive
  • where · object · optionnel
    Exact field matches by dot path, e.g. {"side":"buy"}, {"member.state":"CA"}, {"code":"P"}, {"formType":"4"}; string comparisons are case-insensitive, arrays match when any element does
  • years · array · optionnel
    Event years to read (max 8); default is the newest year with data. Prefer one year at a time for deep-history datasets.
  • offset · integer · optionnel
    Rows to skip, for paging (default 0)
  • ticker · string · optionnel
    Trading symbol, case-insensitive (e.g. 'NVDA'); matches the dataset's ticker field(s). Only datasets flagged tickerSearchable carry tickers.
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
  • dataset · string · requis · congress-trades | insider-transactions | thirteenf-holdings | gov-contracts | gov-grants | lobbying-filings | short-volume | committee-assignments
    Dataset id, from trackers_datasets

  Exemple d'appel

  {"name": "trackers_query", "arguments": {"context": "texte", "dataset": "congress-trades"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

• trackers_ticker≈ 484 tokens

  One ticker across every ticker-bearing Market Trackers dataset for one year (default: the current year): insider transactions, congressional trades, 13F holdings, federal contracts and grants, lobbying filings by the company, short-sale volume, clinical trials, FDA events, patents, Wikipedia pageviews. Returns per-dataset match counts with the newest rows of each — a public-record dossier from primary sources. Deep-history archive years too large for one fan-out are listed under skipped with the trackers_query call that reads them.

  Paramètres, retour & exemple (4)

  Paramètres

  • year · integer · optionnel
    Event year to read (default: the current year)
  • limit · integer · optionnel
    Newest rows to include per dataset (default 5)
  • ticker · string · requis
    Trading symbol, e.g. 'NVDA'
  • context · string · requis
    Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

  Exemple d'appel

  {"name": "trackers_ticker", "arguments": {"ticker": "texte", "context": "texte"}}

  Exemple de retour

  {"content": [{"type": "text", "text": "…"}]}

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Source

https://mcp.luxalgo.com/mcp