generate_dialogue

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

No annotations are provided, so description carries the burden. It discloses async behavior (returns job_id and queued status, with check_jobs returning the audio path), seed determinism, and support for v3 audio tags. It does not mention error handling beyond an error object or permission/authorization needs, but covers key behavioral traits.

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 well-structured with a one-line summary, benefit statement, constraints, an Args list, and a Returns section. It is detailed but every sentence adds value, with no filler.

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 annotations, no output schema, and 7 parameters with 0% schema coverage, the description provides all necessary context: purpose, usage, parameter semantics, constraints, and return/status behavior. It is fully sufficient for an agent to invoke the tool correctly.

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 0%, and the description fully compensates by explaining every parameter with types, defaults, and examples. For lines, it details the structure and optional fields; for apply_text_normalization, it lists enum options; and for engine, it explains the provider override.

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+resource: 'Generate a multi-speaker dialogue scene in a single call.' It distinguishes from siblings by explicitly comparing to generate_speech ('better than stitching N separate generate_speech calls').

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?

Explicitly names alternative generate_speech and explains why this tool is preferred for multi-speaker scenes. Also gives constraints (up to 10 voices, ~2000 chars), providing clear context for when to use it.

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