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trading-research-agents

Official

Show the kill ledger

show_ledger
Read-only

List every standing verdict and its count from the kill ledger. Read-only overview of research memory for the complete picture.

Instructions

List the kill ledger: every verdict that stands, and the count per verdict.

The ledger is the research memory: what was falsified, closed, not proven or validated, on
which axis, and at which fee it would reverse. A retracted row is left out. Use it for the
whole picture; `search_ledger` finds the rows about one idea. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ledger_pathNopath to the kill ledger, ledger.jsonlledger.jsonl

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description reinforces with 'Read-only.' Beyond that it discloses non-obvious behavior: retracted rows are excluded, and it explains what each row encodes (what was falsified, closed, not proven or validated, axis, reverse fee). It does not cover pagination or volume limits, so not a 5.

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 the action and contents; the exclusion and the routing hint are tight. The middle sentence is expository domain framing ('the research memory') that is useful but slightly longer than strictly necessary.

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?

With an output schema present, return values needn't be spelled out. The description covers scope, what is included/excluded, and how to choose between it and `search_ledger`, which is everything an agent needs to invoke it correctly.

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 description coverage is 100% and the single `ledger_path` parameter has a default documented in the schema, so structured data carries the semantics. The description never mentions the path argument or its default, adding nothing on this dimension — baseline 3.

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 and resource ('List the kill ledger') plus the exact contents returned (every standing verdict and the count per verdict). It also implicitly separates itself from `search_ledger` by naming the alternative and its narrower scope.

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

Usage Guidelines5/5

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

Explicit usage rule: 'Use it for the whole picture; `search_ledger` finds the rows about one idea.' The condition selecting this tool versus the sibling is unambiguous, and the exclusion rule ('A retracted row is left out') further bounds expected results.

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