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Search Committees

search_committees
Read-onlyIdempotent

Search political committees (PACs, Super PACs, party committees) by name. Returns committee ID, name, type, designation, party, treasurer, and associated candidates. Example: search_committees("ActBlue")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesCommittee name to search (e.g., "Americans for Prosperity")
_apiKeyYesOpenFEC API key

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query used
totalYesTotal count of committees matching search criteria
returnedYesNumber of committees returned in this response
committeesYesArray of committee records

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-open-fec-api-key",
      -    "query": "ActBlue"
      -  }
      -]New value: +[
      +  {
      +    "query": "ActBlue"
      +  }
      +]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it returns a list of committee details and associated candidates, which is useful. However, it does not disclose pagination, result limits, or behavior when no match is found—minor gaps given the annotations.

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 two sentences with a clear example, no filler, and the most important information (what it searches and what it returns) is front-loaded. Every sentence earns 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?

Given the output schema exists and annotations cover safety, the description is nearly complete. It could mention result limits or pagination, but for a simple search tool with a clear example and return field list, nothing critical is missing.

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 both parameters (query and _apiKey) are already documented. The description adds a concrete example and clarifies that query is a committee name, but it does not go beyond the schema's own parameter descriptions. Baseline 3 is appropriate.

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 clearly states the tool searches political committees by name, lists the specific entity types (PACs, Super PACs, party committees), and enumerates the returned fields. It also provides a concrete example call, making the tool's purpose immediately obvious and distinguishable from sibling tools like search_candidates and search_contributions.

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?

The description implies usage by name search and gives an example, but it does not explicitly state when to prefer this over alternatives like search_candidates or committee_financials. The context is clear enough for an agent to infer the right use case, but explicit exclusions or alternative routing would be stronger.

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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