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Insider transactions

get_insider_trades
Read-onlyIdempotent

Form 4 insider trades for one company, P and S first: who, role, code (P buy, S sell, A grant, M exercise, F tax), shares and dollar value. Use when the user asks: are insiders buying X; did X's CEO sell; insider activity at X. Not for: Congress → get_congress_trades. Args: entity; start; end; limit.

Input Schema

NameRequiredDescriptionDefault
endNoLatest transaction date, YYYY-MM-DD.
limitNoMost transactions, open-market buys and sales first to return.
startNoEarliest transaction date, YYYY-MM-DD.
entityYesThe company: a ticker (AAPL, BRK.B), a company name (Apple) or an SEC CIK.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limit / description
      Previous value: -"Most transactions, newest first to return."New value: +"Most transactions, open-market buys and sales first to return."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds real behavioral value beyond that: the data source (Form 4) and the result ordering ('P and S first'), which tells the agent what a truncated result set will and won't contain. It stops short of describing pagination or date-default behavior, keeping it off 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 core purpose, then usage, then exclusion, then args — a clean scan order with no filler sentences. The trailing arg list is mildly redundant with the schema and is the only thing that doesn't fully earn its place.

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?

With an output schema present, return values needn't be explained, yet the description still names the returned fields and ordering. Combined with the sibling exclusion and the usage triggers, an agent has everything needed to call it correctly; only edge behaviors like pagination or unbounded date ranges are left unstated.

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%, so entity, start, end and limit are already documented with formats and defaults. The 'Args: entity; start; end; limit' line merely restates the parameter names without adding meaning, which is the baseline-3 case when the schema does the heavy lifting.

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+resource with source ('Form 4 insider trades for one company') and even previews the record shape (who, role, code, shares, dollar value). The parenthetical code legend (P buy, S sell, A grant, M exercise, F tax) makes the domain unmistakable and clearly separates it from get_congress_trades.

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?

Gives concrete user-question triggers ('are insiders buying X', 'did X's CEO sell', 'insider activity at X') and an explicit exclusion with the correct alternative ('Not for: Congress → get_congress_trades'). Both the when and the when-not are stated, so no inference is required.

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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