Attach human or caller assessment to a specific audio probe, using metadata inference when direct listening isn't performed.
Append caller or human assessment tied to exact probe audio. Use metadata_inference if the audio was not listened to.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | Yes | ||
| uses | Yes | ||
| method | Yes | ||
| probe_id | Yes | ||
| reviewer | Yes | ||
| confidence | Yes | ||
| description | Yes | ||
| audio_sha256 | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It states a mutation ('append') but does not mention side effects, permissions, reversibility, failure behavior, or return value. This is a significant gap for a write operation.
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?
Two sentences with zero waste. The core action is front-loaded, and the conditional guidance is concise. Every word earns its place.
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 mutation tool with 8 required parameters, no output schema, and no annotations, the description is far from complete. It omits return behavior, error handling, prerequisites, and semantics for most parameters, leaving agents to guess critical details.
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%, so the description must compensate for 8 undocumented parameters. It adds meaning for method (via 'metadata_inference') and implies probe_id/audio_sha256 ('tied to exact probe audio'), but leaves description, reviewer, confidence, uses, and tags unexplained. This is insufficient for an 8-param tool.
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 action 'append' and the resource 'caller or human assessment tied to exact probe audio'. It distinguishes the tool's function from search/probe siblings by focusing on assessment, though it does not explicitly name any sibling.
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?
It gives explicit guidance for the method parameter: 'Use metadata_inference if the audio was not listened to.' This clarifies a key conditional. However, it does not state when to use this tool over alternatives like sound_search or instrument_probe, nor does it provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.