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

Annotations indicate read-only and non-destructive behavior. The description adds context by specifying the data source (FEC public disclosure) and the nature of the data (receipts, disbursements, cash-on-hand). No contradictions 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.

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

Two sentences clearly and efficiently convey the tool's purpose and filtering options. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the existence of an output schema and annotations, the description provides sufficient context for a simple data retrieval tool. It covers what data is returned and how to filter, though it omits details like default ordering or pagination behavior.

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

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

Schema coverage is 100%, so baseline is 3. The description only mentions 'cycle' and 'committee_type' as filters without adding extra meaning beyond the schema's detailed descriptions of each parameter. It does not explain pagination parameters.

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

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

The description clearly states the tool retrieves receipts, disbursements, and cash-on-hand for US political committees, specifying types (PACs, parties, candidate committees). It differentiates from sibling tools like gov.fec.candidates and gov.fec.elections, which cover different aspects of FEC data.

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

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

The description mentions filtering by cycle and committee type, implying the tool is for financial totals. It does not explicitly state when not to use or provide alternatives, but the context of sibling names helps in selection.

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