face_detection_retrieve_details

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

No annotations are provided, so the description carries the behavioral burden. It clearly describes a read-style operation returning a list of faces and includes useful downstream integration context. However, it never explicitly confirms no side effects, nor does it cover auth, rate limits, or task-completion expectations, leaving some behavior to inference.

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, each earning its place: the first states the operation and the second adds the concrete use case with supporting links. There is no filler, no redundant schema repetition, and the core meaning is front-loaded.

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?

With a one-parameter schema at 100% coverage and an output schema present, the description is nearly complete: it explains what is returned, when to use the tool, and how the result feeds into face swap APIs. The only minor omission is explicit guidance about prerequisite task state, but the id provenance is already documented in the schema.

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%, so the baseline applies. The description adds no extra parameter detail, but the schema's id field already documents its provenance ('returned by the face detection API'). An agent can correctly supply the required ID using only 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?

States a clear verb-resource pair: 'Get the details of a face detection task.' The second sentence clarifies the exact payload (list of detected faces) and downstream use, distinguishing it from the sibling face_detection_detect_faces, which creates a detection task. There is no ambiguity about what this tool retrieves.

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?

Provides explicit usage context: 'Use this API to get the list of faces detected... to use in face swap photo/video API calls for multi-face swaps.' This tells an agent when to call it. It does not spell out when not to use it or name a direct alternative for task creation, so it falls just short of a 5.

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