sessions

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

The description adds two pieces of real behavioral context beyond the annotations: deletion is scoped to local storage and never touches upstream OpenAI data, and instructions/response contents are stripped from returned metadata. The destructiveHint=true annotation is consistent with the capitalized DELETE, though the description could say whether deletion is reversible or what a get returns for a missing id.

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?

Three short sentences, front-loaded with the operation list, and every clause carries information (the upstream-data caveat and the metadata exclusion rule are both load-bearing). The only minor waste is the capitalized DELETE, which reads as emphasis rather than content.

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 four-operation tool with annotations and an output schema, the description covers the operation set, the scope of destruction, and the shape of returned metadata. Remaining gaps (pagination via after/limit, per-operation prerequisites) are secondary given the oneOf schema already constrains 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?

Schema coverage is 100%, so session_id, after, limit, and the configure fields are already documented structurally; the description adds nothing per-parameter. Baseline 3 applies, since 'configure defaults' only loosely hints at what model/verbosity/reasoning_effort/timeout_ms are for.

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 names each operation explicitly (list/get metadata, configure defaults, delete) against a specific resource, which is exactly what an agent needs for a single multiplexed tool. 'Local session data' vs 'upstream OpenAI data' also distinguishes it from the chat and request_status siblings, which act on conversation content rather than session records.

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?

Operation names imply which variant to pick, and the schema's oneOf makes the required fields per operation unambiguous. However, there is no explicit guidance on when to list vs get vs configure, nor any statement of prerequisites (e.g., must a session exist before configuring it), and no exclusion rules beyond the upstream-data caveat.

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