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FEC Committee Totals

gov.fec.committee_totals
Read-onlyIdempotent

Access financial totals for US political committees: receipts, disbursements, cash-on-hand. Filter by election cycle and committee type (presidential, House, Senate, party, PAC, Super PAC). Based on FEC public disclosure.

Instructions

Receipts, disbursements, and cash-on-hand for US political committees (PACs, parties, candidate committees). Filter by cycle and committee type. FEC public disclosure

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cycleNoElection cycle year (e.g. 2024).
committee_typeNoCommittee type code: "P" Presidential, "H" House, "S" Senate, "X" Party, "Y" Party-Qualified, "N" PAC, "Q" PAC-Qualified, "O" Super PAC.
pageNoPage number (default 1).
per_pageNoPer-page count (default 20, max 100).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior3/5

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

Annotations already provide readOnlyHint, destructiveHint false, idempotentHint true. The description adds that it returns receipts, disbursements, cash-on-hand, which is useful context but does not disclose behavior beyond basic data content (e.g., no mention of pagination or rate limits). No contradiction with 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?

Two clear sentences with no wasted words. The description is front-loaded with the main purpose and includes filtering options concisely.

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 presence of an output schema and comprehensive annotations, the description is mostly complete for a simple data query tool. It covers the core data returned, though it could mention pagination or that it's read-only (but annotations cover that).

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 the schema already documents parameters. The description mentions 'filter by cycle and committee type' but adds no new semantic meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns receipts, disbursements, and cash-on-hand for political committees, which is a specific resource. It mentions filtering by cycle and committee type, but does not differentiate from sibling FEC tools like gov.fec.candidates or gov.fec.elections.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives (e.g., gov.fec.candidates). It merely describes filtering capabilities, giving no context for when not to use it.

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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