query_requests

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

No annotations provided, and the description does not disclose behavioral traits beyond the basic listing function. It does not mention pagination behavior beyond 'limit', rate limits, auth requirements, or what happens if no results match. The description is adequate but lacks depth for a tool with no annotations.

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?

Two sentences, minimal and well-structured. First sentence states purpose and output fields; second sentence gives usage guidance. No redundant or extraneous information.

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, but the description mentions the fields returned. However, it lacks details on default ordering, sorting, or full response structure. Given the tool has 6 parameters and no output schema, the description could be more complete, but it covers essential purpose adequately.

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% with each parameter already described. The tool description restates filter options (e.g., 'recent ones, errors only, particular model') but adds no new semantic meaning beyond what the schema already provides. 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?

Clear verb ('List'), specific resource ('individual LLM requests'), and explicit fields returned (cost, latency, model, status, error message). Distinguishes from sibling tools like get_stats or list_traces by focusing on individual requests with detailed attributes.

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 when to use: 'when the user wants to see specific calls' and provides concrete examples (recent ones, errors only, particular model, particular user). Does not explicitly state when not to use, but the context and sibling names imply this is for detailed request-level queries.

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