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

With no annotations provided, the description carries the full disclosure burden. It discloses the multi-step pipeline (three LLMs joined together), the output being saved to disk with a file path in the result, and the payment model (deposit, settlement at actual cost + 20%, no account needed). It also includes an example runtime and cost, providing concrete behavioral 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 long but information-dense, structured with an initial summary, a flow sequence, and a cost section. The first sentence gives the essence, and subsequent sentences add essential operational details (output location, payment model, performance). It is somewhat dense and could be slightly tightened, but every sentence provides unique value for such a complex tool.

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 complex tool with no output schema and no annotations, the description covers the creative pipeline, output format (audio, file path), payment requirements, and runtime. It lacks explicit failure modes or a detailed response format beyond the file path, but the given context is sufficient for an agent to invoke the tool correctly and understand the major implications (cost, disk output).

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?

The input schema already covers 100% of the parameters with specific defaults and descriptions. The description adds a flow diagram that names three parameters (Song Instructions, Bands, Style System Prompt) and shows their role in the pipeline, but it does not explain parameter syntax or values beyond what the schema states. This is a baseline 3 with minor extra context.

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 first sentence clearly states the tool's function: it fans out an idea to three LLMs (lyrics, style, negative prompt) and then 'a music model sings it', producing audio. The flow diagram and output description further specify that it returns a file path. This clearly distinguishes it from all sibling tools, which are exclusively image/video generation tools.

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 provides clear context: it is used to convert song instructions into an audio file, with explicit cost and output details. It does not explicitly state when to use it over alternatives, but because none of the sibling tools produce audio, the usage is implicitly unique. No exclusions or alternative recommendations are given, keeping it just below a 5.

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