project_query

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: results are ranked leads rather than verified claims, text output is truncated at 6000 chars with truncation stated, and output structure differs by format.

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 dense but efficient, with the core purpose front-loaded and format-specific details following. Every clause contributes information about behavior or output; it is not padded. It could be slightly more readable by splitting into shorter sentences, but no sentence is wasted.

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 read-only search tool with three well-documented parameters and no output schema, the description covers the essential behavior: what is searched, how results are ranked, how each format behaves, truncation limits, and the caveat that hits are leads rather than verified claims. It might be marginally more complete with a concrete JSON item shape, but the current description is sufficient for correct invocation.

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 documents all three parameters with enum and defaults, so the baseline is 3. The description adds meaning beyond the schema by explaining what the `format` values actually produce (skeleton-first plain text vs. items with reasons) and by clarifying that `question` can be a question, symbol, or file name.

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 a specific verb and resource: it returns 'best code locations for a question', ranked by the passage index. It frames the use case as 'Where is X / what handles Y', which distinguishes it from sibling inspection/analysis tools like node_inspect and analyze.

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 gives a clear context for when to use it (locating code relevant to a question) and even distinguishes human-readable text output from programmatic JSON output. However, it does not explicitly name alternative tools or state when not to use this tool, leaving sibling differentiation to inference.

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