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

Annotations declare readOnlyHint and openWorldHint, and the description adds behavioral context: entity resolution fuzzy match, checking rep votes, and noting correlations vs. causation. No contradictions exist, and the description expands on the read-only nature.

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 three sentences, front-loaded with the main action, and no wasted words. It is concise but could be structured to list steps more clearly. Still, it earns its sentences.

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?

No output schema is provided. The description explains the analysis steps but does not describe the output format (e.g., table, list, chart). Given the complexity of cross-referencing multiple sources, the agent lacks guidance on interpreting results.

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?

Input schema provides descriptions for both parameters (stateCode and districtNumber) and coverage is 100%. The description adds context by mentioning 'in a state' and 'district representative,' aligning with parameters but adding no additional syntax or format details beyond schema.

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 cross-references top complained-about companies with lobbying registrants and campaign contributions, and checks votes on Finance-related legislation. It distinguishes from sibling get_* tools by being an analysis tool, and from other analyze_* tools by specifying the consumer protection focus and methodology.

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 'Shows correlations only — not causation,' which provides a use caveat. However, it does not explicitly state when to use this tool versus other analyze tools (e.g., analyze_energy_policy_influence) or provide when-not-to-use guidance. Usage context is implied but not explicit.

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