get_complaints

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

With no annotations, the description discloses that the tool returns totals per component and truncated narratives, and is non-destructive. However, it doesn't mention rate limits or data freshness, but the behavioral description is adequate for a query tool.

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?

Four concise sentences, front-loaded with the purpose, followed by usage guidance, output description, and a practical hint. No wasted words.

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 an output schema exists, the description adequately explains the output structure (grouped by component, totals, truncated narratives). It covers when to use and gives a usage hint. Missing details like error conditions but otherwise 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 description coverage is 0%, and the description only mentions the limit parameter ('Increase limit for more narratives'). It does not elaborate on make, model, or model_year, leaving them self-explanatory but not adding extra meaning.

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 it retrieves consumer complaints for a vehicle grouped by component, specifying the data source (NHTSA). It distinguishes from sibling tools like recalls, VIN decoding, and safety ratings by focusing on owner-reported problems.

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?

Explicitly says to call when the user asks about known problems, reliability issues, or defects. Offers a hint to increase limit for more narratives. While it doesn't mention when not to use, the context is clear.

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