auto_cleanup_vocal

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

Description mentions async execution with job_id, pipeline steps, and noise profile requirement. It explains that verify costs extra exports. However, it does not disclose if the tool is destructive (modifies original audio) or how to access results beyond monitoring.

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?

Description is well-structured with sections for purpose, pipeline, and args. It front-loads key info but is slightly verbose. Every sentence adds value, though some details could be condensed.

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 two boolean params and async behavior, description covers pipeline and usage but lacks clarity on final output (e.g., what happens to audio file). No output schema exists, so description should explain result format more fully.

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 has two booleans with defaults (0% description coverage), but description adds meaning: remove_noise uses first 0.5s as noise profile, verify measures before/after and costs exports. This compensates well for lacking schema descriptions.

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?

Description clearly states it performs 'professional processing for singing and studio vocals' and lists the pipeline steps. It distinguishes itself from sibling tools like auto_cleanup_podcast and auto_cleanup_interview by specifying vocal focus.

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?

Description explicitly says to use check_pipeline_status to monitor and warns not to call again if a pipeline is running. It also advises setting verify to False on long projects. However, it doesn't explicitly state when to avoid this tool (e.g., for non-vocal material) or compare with alternatives.

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