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TradingAgents MCP

TradingAgents MCP

by ceharsh24

unsettled_decisions

Lists logged investment decisions whose holding windows have traded, showing realised return and alpha versus the regional benchmark, while flagging decisions still waiting.

Instructions

Logged decisions whose holding window has now traded, with their realised raw return and alpha against the regional benchmark. For each, write a short reflection (what the call got right or wrong, and the lesson) and record it with settle_decision. Decisions still inside their window are listed as waiting.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "unsettled_decisions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations at all, the description carries the full burden, and it does disclose meaningful behavior: the listing includes both newly traded windows and still-waiting decisions, plus what metrics come back. It omits ordering, volume/pagination limits, and that this is a non-mutating read, which matters more given the absence of a readOnlyHint.

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?

Three sentences, front-loaded with what is returned, then the required follow-up action. Each sentence carries information (payload contents, action, waiting-state caveat), with only mild redundancy around the reflection guidance.

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

Completeness4/5

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

An output schema exists, so return values need not be spelled out, yet the description still summarizes them and explains the waiting-state edge case. Combined with the pointer to settle_decision, an agent has what it needs; only ordering/limit details are missing.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless schema applies. No misleading hints about filtering or arguments are given.

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

Purpose4/5

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

The description names a specific resource and scope: logged decisions whose holding window has traded, including realised raw return and alpha versus a regional benchmark. That is concrete enough to distinguish it from past_decisions (settled history), though it never names that sibling explicitly, so the differentiation is inferred rather than stated.

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?

It gives a clear workflow context: read these entries, write a reflection on what the call got right or wrong, then record it with settle_decision. That effectively tells the agent when this tool is the entry point. It stops short of explicit exclusions (e.g. 'do not use for already-settled history, use past_decisions').

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