auto_cleanup_interview

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

No annotations are provided, so the description carries the full disclosure burden. It successfully explains async behavior ('Runs in background — returns a job_id immediately'), detailed processing pipeline (DC offset > HPF 80Hz > NR 8dB > compression 2.5:1), and critical prerequisites ('first 0.5 seconds should be room tone / silence' when remove_noise is true). It also warns about concurrency constraints.

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?

Efficiently structured with visual hierarchy: header establishes purpose, async behavior is stated upfront, pipeline details justify the 'light-touch' claim, Args section compensates for schema gaps, and IMPORTANT warnings prevent misuse. No redundancy; every sentence adds value beyond the structured fields.

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?

Despite zero schema descriptions, no annotations, and no output schema, the description is functionally complete. It explains the return value (job_id), monitoring mechanism (check_pipeline_status), parameter defaults, and operational prerequisites. The processing pipeline transparency satisfies the complexity of this multi-stage audio tool.

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% (no property descriptions), but the description fully compensates by documenting both boolean parameters with semantic meaning ('Apply noise reduction using first 0.5s as noise profile' and 'Truncate long silences') plus critical usage constraints that the schema cannot express (the 0.5s silence prerequisite tied to remove_noise).

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 opens with specific verb-noun combination ('ONE-CLICK INTERVIEW CLEANUP') and immediately scopes to 'dialogue and multiple speakers.' It explicitly differentiates from the sibling auto_cleanup_podcast by stating it is 'Lighter than podcast' and 'preserves natural conversation dynamics,' giving the agent clear selection criteria.

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?

Provides explicit workflow guidance: 'Use check_pipeline_status to monitor' and a clear exclusion rule: 'DO NOT call this again if a pipeline is already running — use check_pipeline_status instead.' It also distinguishes from the podcast variant via processing intensity comparison, helping the agent select the correct cleanup tool.

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