resemble_create_detection

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

No annotations are present, so the description must carry the behavioral disclosure. It mentions the wait flag's effect ('response includes a completed verdict when possible') and that Optional flags map to the Detect API, but it fails to disclose other behavioral aspects such as async processing, file retention, rate limits, or error handling. It covers only a subset of the tool's behavior.

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 exactly two sentences, with the purpose front-loaded in the first sentence and the essential usage details in the second. There is no redundant information or filler. It is appropriately concise for a tool of this complexity.

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 the tool's complexity (12 parameters, 0% schema coverage, no annotations), the description is incomplete. It covers the primary usage (submitting a URL or file path, wait behavior, and mapping of some flags) but omits explanations for several parameters (modality, signal, face_only, zero_retention_mode, infer_from_intelligence) and does not mention prerequisites like authentication. An agent would struggle to correctly invoke this tool for all intended use cases.

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%, so the description must compensate. It explains the relationship between url and file_path, and it maps some optional flags (intelligence, watermark, source-tracing, reverse-search) to the Detect API, but it does not explain the other six parameters (signal, modality, face_only, zero_retention_mode, infer_from_intelligence). With 12 parameters and no schema descriptions, the explanation is insufficient for an agent to understand all parameters.

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 tool's purpose: 'Submit a deepfake detection job for audio, image, or video.' This is a specific verb (submit) with a clear resource (deepfake detection job) and modality. It effectively distinguishes from siblings like resemble_get_detection, which imply retrieval rather than creation. The description leaves no ambiguity about the action.

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 provides practical parameter-level guidance, such as 'Provide exactly one of url or file_path' and the effect of wait=True on the response. However, it does not explicitly state when to prefer this tool over alternatives (e.g., resemble_secure_upload for uploading files) or give any exclusions. The usage context is implied but not directly articulated.

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