InsiderTrack MCP

member_track_record

Read-onlyIdempotent

Measure how a politician's disclosed stock buys and sales performed versus SPY at 30, 60, and 90 days after disclosure.

Instructions

How a member of Congress's disclosed stock buys (and sales) actually performed.

Every buy is measured from the first close after disclosure at 30/60/90 days, against SPY over the same days. weight_in_score is what that record earns the member's trades in the composite score (1.0 = neutral). Sales are measured the same way (a good sale is one the stock then fell).

Args: politician_id: From search. recent_trades: Measured buys to list, 0-50 (default 10).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`politician_id`	Yes
`recent_trades`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 20, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint true and idempotentHint true, so safety profile is covered. The description adds valuable behavioral context: measurement window (first close after disclosure, 30/60/90 days), comparison against SPY, meaning of weight_in_score, and treatment of sales. No contradiction.

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

Conciseness5/5

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

Description is compact and front-loaded with purpose, then methodology, then parameter guidance. Every sentence contributes; no filler.

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?

Given output schema exists and annotations cover read-only behavior, the description is sufficient. It covers purpose, measurement methodology, and parameter semantics. Minor gaps like error handling are not necessary because of output schema.

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

Parameters5/5

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

Schema description coverage is 0%, so description carries full parameter documentation burden. It adds meaning beyond schema: politician_id sourced from search, recent_trades defined as measured buys with range 0-50 and default.

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?

Description states a specific verb+resource: it evaluates how a member's disclosed stock trades performed, with defined measurement methodology. It distinguishes from sibling tools like search and leaderboard by focusing on individual member trade performance.

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?

Description clearly implies usage: to get performance of a specific member's trades, and references 'search' as source of politician_id. It does not explicitly compare against alternatives or state when-not-to-use, but the context is clear enough.

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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