reprocess_face

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does ('reprocess') and the intended outcome ('update predictions'), but does not disclose side effects, whether it modifies or deletes the image, whether it triggers recomputation of embeddings, or any permissions required.

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 a single, concise sentence that front-loads the primary action and result. There is no redundant wording or filler, making it easy to parse.

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?

Despite being a simple one-parameter tool with an output schema, the description lacks critical context for a state-changing operation. It does not explain what 'reprocess' entails, whether it is destructive or reversible, how long it takes, or what the response contains. This is inadequate for an agent that needs to invoke it safely.

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?

The schema already provides a 100% coverage description for the single parameter (training_file), so the baseline is 3. The tool description adds 'to update predictions' which gives context for why the parameter matters, but does not add new semantic detail beyond 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 clearly identifies the action ('Reprocess'), the resource ('a face training image'), and the purpose ('to update predictions'). This is specific and distinguishes it from sibling tools like reprocess_event_license_plate (which targets license plates) and rename_face (which renames).

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?

No guidance is provided on when to use this tool versus alternatives, such as after adding new face images or when predictions are stale. It does not mention prerequisites (e.g., having a training image in the faces/train directory) or conditions that warrant reprocessing.

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