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lzinga

US Government Open Data MCP

fec_search_committees

Read-only

Search for political committees (PACs, campaign committees, party committees) by name, state, or type. Use committee_type='Q' with a company name to identify corporate PAC IDs.

Instructions

Search for political committees (PACs, campaign committees, party committees) by name, state, or type. CRITICAL for investigations: Use committee_type='Q' (Qualified PAC) + name='Company Name' to find corporate PAC IDs. Example: name='Wells Fargo', committee_type='Q' returns C00034595 (Wells Fargo Employee PAC). Then use fec_committee_disbursements with the committee_id to trace money to specific politicians.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoCommittee name to search for
stateNoTwo-letter state code
committee_typeNoCommittee type: 'P' (Presidential), 'H' (House), 'S' (Senate), 'N' (PAC - Nonqualified), 'Q' (PAC - Qualified), 'X' (Party - Nonqualified), 'Y' (Party - Qualified), 'I' (Independent Expenditor), 'O' (Super PAC)
cycleNoTwo-year election cycle, e.g. 2024
pageNoPage number (default: 1)
per_pageNoResults per page (default: 20)
Behavior3/5

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

Annotations indicate readOnlyHint=true, and the description does not contradict this. However, it adds no additional behavioral traits (e.g., pagination behavior, error cases, authentication requirements) beyond what annotations provide. The description focuses on usage patterns rather than systemic behavior.

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 three sentences: general purpose, critical guidance, and an explicit example. It is front-loaded with the most important information and contains no superfluous text.

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 tool has no output schema, the description provides a concrete example and chains to a complementary tool (fec_committee_disbursements). It does not cover pagination or response format, but these are partially covered by the schema and annotations. Overall, it is adequate for an agent to understand usage.

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?

Input schema has 100% description coverage; the description does not add new semantic meaning to individual parameters. It emphasizes a specific parameter combination (committee_type='Q' + name) as a usage hint, but this is not parameter-level semantics.

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 verb 'Search' and the resource 'political committees (PACs, campaign committees, party committees)'. It distinguishes from sibling tools like fec_search_candidates and fec_committee_disbursements by specifying the target resource.

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 provides explicit guidance for investigations, highlighting the critical use of committee_type='Q' with a company name, and directs the agent to subsequently use fec_committee_disbursements. It does not explicitly state when not to use the tool, but the context is clear.

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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