FEC Campaign Finance

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

No annotations provided, so description carries full burden. It discloses that the tool returns fundraising totals, cash on hand, and spending, which is good. However, it does not mention authentication, rate limits, data freshness, or pagination behavior.

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 concise with two sentences, front-loaded with the purpose and followed by key details. No extraneous words, every sentence earns its place.

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 no output schema, the description adequately explains the return values. It covers filtering options and data types. However, it could mention that name is a search parameter and that limit has a maximum, but these are in the schema. Overall, it is fairly complete.

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 meaning beyond the schema by explaining what the tool returns (fundraising totals, cash on hand, spending) and how filters relate to that output. This extra context justifies a higher score.

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 gets FEC campaign finance data for federal election candidates and specifies the returned data (fundraising totals, cash on hand, spending) and filtering options. It distinguishes from siblings like get_fec_donors and get_fec_spending by focusing on candidates.

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 data but does not explicitly state when to use this tool over siblings or provide exclusions. It lacks explicit when-to-use or when-not-to-use guidance.

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 carries full burden for behavioral disclosure. It does not mention any behavioral traits such as rate limits, authentication requirements, or whether the operation is read-only. The description is minimal and leaves the agent unaware of important constraints.

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 extremely concise—two sentences that immediately convey the tool's purpose. Every sentence earns its place with no wasted words or fluff.

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 complexity (7 parameters, no output schema, no required fields), the description is too minimal. It does not explain how parameters relate (e.g., need candidate_id or committee_id?), expected output format, or any usage patterns. The agent lacks essential context to use the tool effectively.

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?

The input schema has 100% description coverage for all 7 parameters. The tool description does not add any additional meaning beyond what is already in the schema, so the baseline score of 3 is appropriate.

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. It uses a specific verb ('get') and resource ('donor/contribution data'), and the context of sibling tools (get_fec_candidates, get_fec_spending) further distinguishes its purpose.

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 when donor data is needed but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_fec_candidates, get_fec_spending), nor any conditions or exclusions. Usage is left inferred.

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 bears full responsibility for disclosing behavioral traits. It mentions 'Get campaign spending data' but does not specify if the tool is read-only, has authentication requirements, rate limits, or any side effects. The lack of such details limits 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 description consists of two concise sentences that front-load the purpose and then explain the key parameter. No extraneous words or redundancies.

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 5 parameters fully described in the schema and no output schema, the description covers the main usage guidance for the 'type' parameter. It is sufficient for a straightforward data retrieval tool, though it could mention pagination or default ordering.

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 description coverage is 100%, baseline 3. The description adds value by explaining the two 'type' options in more contextual language ('Super PAC / outside group spending' vs 'direct campaign spending'), which aids understanding beyond the schema's brief 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?

Description clearly states 'Get campaign spending data' and distinguishes two spending types (independent vs expenditures). This differentiates the tool from sibling tools 'get_fec_candidates' and 'get_fec_donors'.

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?

Description explains when to use 'type=independent' versus 'type=expenditures', providing clear guidance on parameter choice. However, it does not explicitly state when not to use this tool or mention alternative tools for other FEC data.

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