media_labeling

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

No annotations exist, so the description must fully disclose behavior. It reveals that the tool uses an async upstream job that is automatically submitted and polled, which is critical for an agent to handle correctly. It also lists many label codes, giving a detailed view of what the tool detects.

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 relatively concise, with the main action in the first sentence and supporting details following. It avoids redundancy, though the list of labels could be slightly more compact. Overall, it's well-structured and 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?

The description explains the purpose and async behavior, but does not describe the return value structure (e.g., whether it returns presence flags, confidence scores, or raw labels). Given the absence of an output schema, this omission reduces completeness for an agent needing to interpret results.

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 baseline is 3. The description adds value by grouping label codes into portrait and environment categories and providing an example, which helps the agent construct valid input beyond the schema's bare descriptions.

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 'Analyze' and the resource 'image/video for risk and scene attributes', listing specific label types. This distinguishes it from sibling tools like face_compare or OCR tools, which have different purposes.

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 explicitly mentions best-use cases (compliance scene checks, loan/insurance evidence review, anti-fraud triage), but does not provide exclusion criteria or contrast with alternatives. The sibling tools are sufficiently different that confusion is unlikely.

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