vocametrix_extract_egemaps

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

No annotations are provided, so the description must fully disclose behavior. It states extraction but omits crucial details such as whether the file is modified, required permissions, output format, or error handling (e.g., missing file or non-WAV format).

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: the first clearly states the core action and scope, the second adds examples and a use case. No unnecessary words; information is front-loaded and efficient.

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 tool is simple with one parameter and no output schema, yet the description fails to mention what the tool returns (e.g., feature values as JSON). This leaves the agent uncertain about the tool's output, which is a significant gap.

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% with a single parameter 'audioPath' described as an absolute WAV path. The description adds context about the feature set and use case but does not enhance parameter semantics beyond the schema's own description.

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 specifies extraction of the full eGeMAPSv02 feature set (88 acoustic features) from an audio file, listing example features and a clear use case for ML voice pathology classifiers. This distinguishes it from sibling tools that extract individual features or perform other audio analyses.

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 implies usage for obtaining a comprehensive acoustic feature set, especially for ML classifiers. However, it does not explicitly state when to use this tool versus the many single-feature siblings, nor does it provide exclusions or alternatives.

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