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

With no annotations provided, the description carries the burden of conveying behavior. It discloses that matching uses literal title matching plus embedding-based semantic similarity, and that results are ranked to favor broad-coverage surveys over niche ones. It does not cover all potential behaviors (e.g., response format, rate limits), but it offers substantial transparency for a read-oriented search 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?

The description is three sentences long, front-loaded with the core purpose, and every sentence adds meaningful detail: what the tool does, how matching handles variations, and how results are ranked. No filler or redundancy.

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 lack of an output schema, the description does enough to set expectations about matching and ranking. It could additionally mention what fields appear in results (e.g., survey report IDs, titles), but for a lookup tool with clear input semantics and a single required parameter, the provided context is strong.

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 schema already covers both parameters (position, limit) at 100% coverage, so the baseline is 3. The description adds value by explaining that 'position' accepts abbreviations and paraphrases, with concrete examples showing how fuzzy matching works, which goes beyond the schema's simple 'Job title or position to look up' and 'free text'.

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 uses a specific verb ('Find') and resource ('compensation surveys') with a clear scoping qualifier ('benchmark a specific job title or position'). It gives concrete examples and explains the matching mechanism, which distinguishes it from sibling tools like search or recommend_surveys.

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 clearly implies when to use this tool: when you have a job title or position to look up, including abbreviations and paraphrases. It provides illustrative examples but does not explicitly state when not to use it or mention alternatives such as 'search' or 'recommend_surveys'.

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