generate_ai_report

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states the purpose and inputs, but fails to mention any behavior traits such as resource consumption, generation time, error conditions (e.g., if the transcript is not yet complete), or data retention. For a tool that generates reports, this lack of transparency could lead to incorrect expectations.

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 sentence that front-loads the action and resource, listing options concisely. No extraneous words; every part is necessary and informative.

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 simple input schema (2 required fields with clear enum) and no output schema, the description provides adequate context for understanding the tool's function. Minor gaps: it does not describe the return format (e.g., text vs. structured data) or error handling, but these are secondary for a straightforward generation tool.

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% and both parameters have descriptions. The description adds context by stating the transcript must be 'completed' for the job_id parameter and enumerates valid type values in the text. This adds meaningful guidance beyond the schema alone, though the schema already covers the basics.

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 verb 'generates' and the resource 'deep AI structural analysis report', listing specific report types (Summary, Action Items, Outline, Speakers). It unequivocally distinguishes the tool from sibling tools like transcribe_audio or get_transcript by specifying it operates on completed transcripts.

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 indicates the tool is meant for 'a completed transcript', giving clear context on when to use it. However, it does not explicitly mention when not to use it or provide alternatives (e.g., if the transcript is incomplete, use get_job_status first). This is a minor gap, but the instruction is clear enough for most agents.

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