llm_request_list

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

Beyond the read-only/idempotent annotations, the description discloses that the tool 'Returns metadata only', that results are sorted 'newest-first', and that it covers both 'sync and async' requests. It also hints at the shape of the response by referencing correlationId and asyncJobId. No contradiction with 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 tight sentences: the first defines the action and ordering, the second defines the return type and onward routing. No filler, every clause carries 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?

Although there is no output schema, the description compensates by telling the agent that the response is metadata-only and how to use the returned identifiers with llm_request_result and llm_job_status. All four optional parameters are fully documented in the schema, and the use case is clear, so nothing needed for a correct call is missing.

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%: each parameter (cli, limit, since, sessionId) already has a clear description with examples/ranges. The tool description adds no parameter-specific detail, so the baseline of 3 applies.

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 opens with a specific verb and resource: 'List recent persisted requests (sync and async) newest-first without a correlation id, to find one.' This states the exact purpose and distinguishes the tool from follow-up tools like llm_request_result and llm_job_status by naming the returned identifiers to pass along.

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?

It gives an explicit when-to-use condition ('without a correlation id, to find one') and explicit routing for the results ('pass a returned correlationId to llm_request_result... or a returned asyncJobId to llm_job_status'). This tells an agent exactly how this list tool fits into the workflow and when to switch to an alternative.

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