Audio fingerprint → visual

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

Discloses the full workflow: sampling, fingerprint extraction, heuristic mapping, parameter tuning, dispatch, and optional compositing via apply_top_op. Also explains the dry_run behavior and the rationale for the synthetic default. No contradictions with annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true).

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 dense paragraph covering the core algorithm, default behavior, and key options. It front-loads the main action, but could be more structured (e.g., bullet points for clarity). Still concise and informative.

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 9 parameters, no output schema, the description explains the algorithm and default rationale but does not describe the normal return value (the generated generator) or details of the heuristic mapping. The gap for normal-case output reduces completeness.

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?

With 100% schema description coverage, the baseline is 3. The description adds value beyond the schema by explaining why 'synthetic' is the default (macOS permission hangs) and clarifying dry_run's purpose (returns mapping without building). This justifies a 4.

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 what the tool does: sample audio, compute a 4-feature fingerprint, run a deterministic heuristic to pick a Layer 1 generator (naming specific options), and dispatch it with tuned parameters. This distinguishes it from sibling create_* tools as an orchestrator.

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 guidance on audio_source defaulting to 'synthetic' to avoid macOS mic-permission hangs, and mentions dry_run for testing. However, it does not explicitly contrast with using individual create_* tools directly, limiting when-not-to-use advice.

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