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Read-onlyIdempotent

Look up members of Congress, tickers, 13F funds, and Fed officials by name or symbol to get the exact IDs needed for other tools. Partial matches work too.

Instructions

Find members of Congress, tickers, 13F funds and Fed officials by name or symbol.

Use this first when you have a name or part of a ticker and need the politician id, fund id or exact symbol that the other tools take. Matching is case-insensitive and partial ("pelosi", "NVD", "berkshire").

Args: query: A name or ticker fragment, 1-80 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior4/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds meaningful behavioral detail: matching is case-insensitive and partial, with concrete examples. This tells the agent how querying will behave, though it does not discuss result limits or ordering, which are minor given the output schema exists.

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?

The description is compact and well-structured: purpose first, usage context second, matching behavior with examples third, and parameter spec last. Every sentence contributes necessary decision-making information with no filler or repetition.

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 single-parameter search tool with an output schema and read-only, idempotent annotations, the description provides the necessary purpose, usage trigger, matching semantics, and parameter constraints. There is no material missing information an agent would need to choose and call the tool successfully.

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?

Despite 0% schema description coverage, the description fully compensates by defining the single parameter: 'A name or ticker fragment, 1-80 characters.' It also implies valid input types and length constraints, so the agent can construct the query correctly without further schema documentation.

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?

The description uses a specific verb ('Find') and explicitly lists the four resource types (members of Congress, tickers, 13F funds, Fed officials), plus the concrete outputs (politician id, fund id, exact symbol). This clearly distinguishes it from the sibling tools that consume those IDs rather than performing lookup.

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?

'Use this first when you have a name or part of a ticker and need the politician id, fund id or exact symbol that the other tools take' is explicit guidance on when to invoke this tool before others. It also frames the tool as a lookup/disambiguation step within the broader toolset.

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