get_face_detection_result

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

With no annotations, the description carries full burden but provides minimal behavioral context. It mentions the return content (face IDs and URLs) but lacks details on error handling, rate limits, authentication needs, or whether it's idempotent. For a read operation with zero annotation coverage, this is inadequate.

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?

The description is two concise sentences with zero waste: the first states the purpose, and the second specifies the return values. It's appropriately sized and front-loaded with essential 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?

Given no annotations and no output schema, the description is minimal but covers the basic purpose and return values. However, for a tool that likely involves async processing and data retrieval, it lacks context on job states, error conditions, or output format details, making it only adequate.

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 the single parameter 'id' documented as 'The face detection job ID'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3.

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 clearly states the verb ('Get') and resource ('result of a face detection job'), specifying it returns 'detected face IDs and URLs'. It distinguishes from siblings like 'detect_faces' (which initiates detection) and status-checking tools, though it doesn't explicitly name alternatives.

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?

The description implies usage after a detection job is completed (by referencing 'job ID'), but doesn't explicitly state when to use this versus alternatives like 'get_image_project_status' or specify prerequisites. No exclusions or clear alternatives are mentioned.

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