fec-donor-intel

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

With no annotations provided, the description carries the full burden. It discloses that results are 'sorted newest-first', includes specific fields (committee names, amounts, cycles, employer/occupation, aggregates), and notes the data source ('Official FEC Open Data, updated daily'). It could mention rate limits or pagination but covers essential behavioral traits.

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?

The description is two sentences long, front-loaded with the core purpose and key details, followed by use cases. Every sentence is valuable and there is no redundancy or filler.

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?

The tool has 3 parameters, no output schema, and no annotations. The description sufficiently outlines the return structure (fields like committee names, amounts, etc.) and includes data freshness. It lacks explicit error handling or data volume notes, but the overall context is adequate for a simple lookup tool.

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 adds meaningful guidance: for the 'name' parameter, it recommends the format 'LAST, FIRST' for individuals; for 'cycle', it explains omission means all cycles; for 'limit', it specifies range and default. This adds value beyond the schema descriptions.

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's purpose: 'FEC campaign finance lookup — search all US federal political donations by individual or organization name.' It specifies the resource (donations) and action (search), and lists the return fields, distinguishing it from siblings like 'company-due-diligence' or 'sanctions-screening' which have different foci.

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 provides explicit use cases: 'Use for executive due diligence, political affiliation screening, ESG analysis, or investigative research.' This guides the agent on appropriate contexts. However, it does not mention when not to use it or suggest alternative tools for related but different queries (e.g., for corporate donations specifically).

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