suno_overpainting

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 that the tool is asynchronous (returns a Task ID) and that it modifies/creates audio with vocals. However, it doesn't mention that the operation is non-destructive to the original upload, whether it consumes credits, or any rate limits. The async nature is disclosed via 'Returns: Task ID', which is useful but minimal.

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 clear summary, use-case bullets, and a returns section. It's slightly longer than necessary—the 'overpainting = painting vocals over the music' parenthetical is helpful but could be trimmed. Overall, every section earns its place and the key info is front-loaded.

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?

The description covers the core purpose, use cases, and return value (Task ID). It doesn't explain polling or callback behavior in detail, but the output schema and parameter descriptions cover the mechanics. For a tool with 5 params and an output schema, this is reasonably complete, though it could mention that the result is delivered asynchronously via task polling.

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 100%, so the schema already documents all 5 parameters. The description adds context for audio_id ('uploaded instrumental track') and explains the overpainting concept, but doesn't add detail beyond the schema for model, callback_url, or the start/end times. Baseline 3 is appropriate since the schema does the heavy lifting.

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's function: adding AI-generated vocals to an uploaded instrumental track. It uses a specific verb ('add'), names the resource ('uploaded instrumental audio'), and explains the metaphor ('overpainting = painting vocals over the music'). This distinguishes it from siblings like suno_underpainting and suno_extract_vocals.

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 explicit use cases ('when you have an instrumental track and want to add vocals', 'want to give background music a singing voice', 'need to add vocal melody to existing music'). It doesn't explicitly state when NOT to use it or name alternative tools, but the use-case list gives clear context for when this tool is appropriate.

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