extract-text-layers

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

With no annotations provided, the description carries the burden and does a good job: it discloses the side effect of saving a working file and specifies the extracted data shape. It does not mention overwrite behavior, file location, or error handling, but the core behavioral impact is transparent.

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?

Two sentences, no filler. The first sentence states the action and output, the second gives the workflow context. Everything earns its place.

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?

For a single-optional-parameter tool with no output schema, the description conveys enough: what is extracted, what is saved, and why it is saved. The 'working file' is vague but the sibling pipeline likely resolves that ambiguity; still, a path or format detail would make it fully complete.

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%, so the optional compName parameter is already fully documented in the schema as limiting to a single composition or scanning the whole project. The description adds little beyond that, so baseline 3 is appropriate.

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?

States a specific verb and resource: 'Extract every text layer' from the open After Effects project, with the exact captured fields listed. This clearly distinguishes it from sibling tools like match-glossary or apply-text-translations, which operate on the extracted result.

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 places the tool in a workflow: it saves a working file 'for the match-glossary step', which tells the agent it is a preparation step before glossary matching. It does not explicitly list exclusions or alternatives, but the pipeline context is clear enough.

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