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longsizhuo

OpenInvest

by longsizhuo
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Python
Hybrid

run_committee

Idempotent

Run a four-role LLM investment committee on any ticker: macro, quant, and risk agents debate, then a CIO issues a BUY/HOLD/SELL verdict with memo for human decision support.

Instructions

Run the 4-role LLM investment committee on a symbol (Direct path): Macro Strategist, Quant Analyst, and Risk Officer debate from isolated evidence, then a CIO synthesizes one calibrated BUY/HOLD/SELL-style verdict with a written memo.

Requires a backend LLM key (e.g. DEEPSEEK_API_KEY) and takes 30-90s on a cache miss. If the symbol was already analyzed today, the cached verdict is returned instantly unless force is set. Sends MCP progress notifications per debate phase when the client asks for them. Decision support only — the human always executes.

Args: symbol: Any yfinance ticker (US / HK / A-share / ETF / crypto / commodities), e.g. "AAPL", "GC=F", "510300.SS". force: Re-run even if a verdict already exists for today. max_rounds: Cross-challenge debate rounds (default 1).

Returns: Object with decision_id, cached flag, verdict and confidence_lookup (show this to the user instead of the self-reported confidence). The shape differs by path: - cached: false (fresh run): verdict is an object (verdict, confidence, suggested allocation, ...). - cached: true (today's transcript): verdict is the verdict string, with confidence, alloc_cny, alloc_currency alongside, plus the CIO memo as cio_memo and the deterministic input_health block (empty inputs, rewrite rules applied, forced HOLD) — no need to call explain_decision just to read them.

Input Schema

NameRequiredDescriptionDefault
forceNoRe-run even if a verdict already exists for today.
symbolYesAny yfinance ticker (US / HK / A-share / ETF / crypto / commodities), e.g. 'AAPL', 'GC=F', '510300.SS'.
max_roundsNoCross-challenge debate rounds.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.34.0
  2. Removedv0.31.6
  3. Changed4 schema fields changedv0.31.4
    • addedInput schema / properties / force / description
      Added value: +"Re-run even if a verdict already exists for today."
    • addedInput schema / properties / max_rounds / description
      Added value: +"Cross-challenge debate rounds."
    • addedInput schema / properties / max_rounds / minimum
      Added value: +1
    • addedInput schema / properties / symbol / description
      Added value: +"Any yfinance ticker (US / HK / A-share / ETF / crypto / commodities), e.g. 'AAPL', 'GC=F', '510300.SS'."
  4. First observedv0.31.0

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds substantial context beyond annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false): backend key requirement, 30-90s latency, today-cache/`force` semantics, MCP progress notifications per phase, and the explicit 'decision support only — the human always executes' boundary.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and requirements before Args/Returns. The Returns section is detailed but informative given the path-dependent shape; slightly verbose, though no sentence is truly wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex multi-phase LLM tool, the description covers latency, caching, progress reporting, auth/key needs, and return-shape differences by path — more than enough even though an output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all three parameters; the description's Args section largely restates them (symbol examples, force, max_rounds default). Marginal added value, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Run the 4-role LLM investment committee') and resource ('on a symbol'), then explains the multi-role debate + CIO synthesis in a way that clearly distinguishes it from siblings like prepare_committee and submit_committee.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context: requires an LLM key, 30-90s on a cache miss, cache is returned unless `force` is set, and labels itself the 'Direct path.' However it never names the alternative path (prepare_committee/submit_committee) or states when to choose this vs. those, so routing between siblings is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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