AgentFEC

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

No annotations are provided, so the description carries the full burden. It states what data is returned but fails to disclose behavioral traits such as rate limits, authentication needs, pagination behavior, or whether the tool is read-only. For a data retrieval tool, this is insufficient transparency.

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 single-sentence description is concise and front-loaded with the core purpose. It conveys key information without extraneous words, though it could be slightly structured (e.g., bullet points) for clarity.

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?

For a tool with 6 well-described parameters and no output schema, the description covers the main returns but omits details on pagination (limit parameter hints at max 50 but no explanation), error handling, or data freshness. Adequate for a simple query tool but leaves gaps given no annotations.

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 restates office codes (P, S, H) and party values (DEM, REP, IND) already present in the schema, adding no new semantic meaning. It adds context on return types (fundraising totals) but that pertains to outputs, not 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 FEC campaign finance data for federal election candidates, specifying return types (fundraising totals, cash on hand, spending) and filter options (office, state, party). It effectively distinguishes from sibling tools 'get_fec_donors' and 'get_fec_spending' by focusing on candidate-level 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 implies usage for candidate finance queries but lacks explicit guidance on when to choose this over 'get_fec_spending' or 'get_fec_donors'. No exclusion criteria or alternatives are mentioned, relying on sibling names to imply differentiation.

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

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

No annotations are provided, so the description alone must inform the agent about behavioral traits. It does not mention that the tool is read-only, whether it supports pagination, or any rate limiting or data freshness. The description is too terse to adequately disclose behavior beyond the basic action.

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 brief, consisting of two short sentences. The first sentence clearly states the function, and the second adds minimal value. It is well-structured but could be more efficient by omitting the second sentence or integrating it.

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?

With 7 parameters, no output schema, and no annotations, the description lacks completeness. It does not explain the return format, pagination behavior, or how the optional filters interact. The agent would have limited understanding of how to effectively use the 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?

All 7 parameters have descriptions in the schema, achieving 100% schema description coverage. The description adds no additional context or guidance on how to combine parameters or the meaning of the return values beyond what the schema already provides, meeting the baseline of 3.

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 individual donor/contribution data from FEC Schedule A filings, specifying the scope (for a candidate or committee) and purpose (finding who funds campaigns). This effectively distinguishes it from sibling tools like get_fec_candidates and get_fec_spending.

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 no guidance on when to use this tool versus the alternatives (e.g., get_fec_candidates, get_fec_spending). It does not mention any prerequisites or scenarios where this tool is appropriate or not.

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

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

No annotations are provided, so the description must fully disclose behavior. It only states what the tool does, not traits like rate limits, authentication needs, pagination behavior, or error handling. This is a significant gap for a tool with no 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?

The description is two sentences with no wasted words. The first sentence gives the general purpose, the second details the main parameter options. Information is front-loaded and efficient.

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?

For a 5-parameter tool with no output schema, the description covers the key distinction (type) and implies the filtering capability. It does not explain interactions between parameters (e.g., candidate_id + committee_id) but the schema covers each parameter individually, making the overall context adequate.

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?

With 100% schema coverage, the schema already describes all parameters. The description adds context by explaining the 'type' parameter's real-world meaning (Super PAC vs direct spending), which enhances understanding beyond the schema's definitions.

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 campaign spending data and distinguishes between two specific types (independent and expenditures). It is distinct from sibling tools (candidates, donors), providing a specific verb+resource combination.

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 explains when to use each type parameter (Super PAC vs direct campaign spending), offering clear context. However, it does not explicitly exclude other scenarios or compare against sibling tools.

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