generate_article_narration

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

No annotations are provided, so the description carries the burden. It discloses the async nature, returns a job ID, and automated voice selection, but does not detail error behavior, cost, or length limits beyond schema.

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?

Three succinct sentences cover purpose, use cases, parameters, and workflow. No wasted words; each sentence adds essential information.

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 no output schema, the description explains the return (job ID) and async behavior. It covers inputs, process, and output, but could briefly mention polling or error handling.

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%, but the description adds value by providing context for defaults (e.g., 'warm and clear' for nova voice, prepending title, maxLength for text). This enhances understanding beyond raw 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 states the tool generates audio narration from article or blog post content, specifying use cases like podcast-style audio, accessibility voiceovers, and audio newsletters. It distinguishes itself from the sibling 'generate_audio' by focusing on article-specific inputs and async job submission.

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 explains when to use the tool (for article narration) but does not explicitly compare to alternatives like 'generate_audio'. It lacks clear guidance on when not to use it or prerequisites.

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