text_to_music

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

No annotations are provided, so the description carries the transparency burden. It does disclose that the tool creates a task and returns a task id, status, and output URLs, which hints at asynchronous task behavior. However, it does not explain side effects, cost implications, authentication needs, or what a terminal status means, so transparency remains partial.

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, front-loaded sentence that states the primary verb, resource, and expected return values. It wastes no words and is easy to scan. The concise structure leaves only the most important details visible.

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 tool with 19 parameters and no output schema or annotations, the description is not fully contextual by itself. It does mention the return shape and the overall purpose, and the schema provides good parameter detail, so the tool is minimally viable for an agent. Still, it lacks guidance on parameter combinations, mode semantics, or operational expectations like async behavior.

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 approximately 89%, and the input schema already provides meaningful descriptions for most parameters. The tool description itself does not add much parameter-level detail beyond the schema, such as how vocal_mode interacts with lyrics or prompt. Since the schema already carries the burden, a baseline score of 3 is appropriate.

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 identifies the tool's action: create a Suno task for text-to-music generation on RunAPI. It also states the key output (task id, status, output URLs). It does not explicitly contrast with sibling tools, but the phrase 'text to music' conveys the primary function well enough.

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 when to use the tool—when a user wants music generated from text via Suno—but it does not provide explicit guidance about when to prefer it over alternatives like text_to_sound, generate_lyrics, or cover_audio. It is minimally useful but lacks explicit exclusions or alternative scenarios.

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