to_grayscale

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only states the conversion action without revealing side effects, whether the input is modified in place, or whether a new clip is returned. This minimal description leaves important behavioral traits unspecified.

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, clear sentence with no redundancy. It front-loads the action and is appropriately sized for the tool's simplicity.

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 simplicity, the description is quite incomplete. It doesn't explain the operation's effect on the original clip, whether it creates a new clip, or how the output is structured, despite the presence of an output schema. The lack of annotations further limits contextual completeness.

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 input schema describes only clip_id, and the description makes no mention of parameters or their roles. With 0% schema description coverage, the description adds no value in explaining the parameter's purpose or format, leaving the agent to rely solely on the property name.

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 function: converting a video/image clip to black and white. It uses a specific verb and resource, and the 'to grayscale' name aligns with the description, differentiating it from siblings like adjust_colors which handle broader color adjustments.

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 usage guidance is provided. The description does not specify when to prefer this tool over alternatives like adjust_colors, nor does it mention any prerequisites or exclusions. The only hint is the action itself, which is not sufficient.

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