chatgpt_list_project_conversations

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds two non-obvious behavioral caveats the annotations cannot express: a single call may not traverse all pages, and pagination only covers query keys that were actually recorded. The vague 'calibrate first' requirement is disclosed but never explained, which keeps it from a 5.

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 compact sentences with no filler, and the project-scoping statement is front-loaded ahead of the caveats. Nothing is wasted, though the terseness leaves the key prerequisite unexplained.

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 tool with a nested pagination object, zero schema coverage, and no output schema, the description covers the pagination limitation but leaves project_id semantics and the calibration prerequisite undefined. An agent would know the tool's rough shape but not how to satisfy the prerequisite or choose among pagination fields.

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 0% and the nested pagination object has four undocumented fields (after, cursor, limit, offset); the description refers to 'pagination parameters' generically without clarifying which field acts as the cursor versus the offset, or how they interact. project_id is never explained beyond pattern constraints in the schema.

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 states a specific verb and resource — reading conversations scoped to a given project — which distinguishes it in substance from the sibling chatgpt_list_conversations. It never names that sibling explicitly, so the differentiation must be inferred from the scope word 项目.

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 a prerequisite ('需先校准该接口'), signaling the tool should not be called cold, but it never names the calibration tool (chatgpt_record_start / preview_changes / execute_plan among the siblings) nor states when to prefer this tool over chatgpt_list_conversations or chatgpt_search_conversations. Usage is implied rather than prescribed.

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