voice_call_quality

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

Annotations provide only a title, so the description carries full burden. It clearly indicates a read-only operation ('Retrieves') and describes the output metric (MOS) with a legend. No side effects or permissions are mentioned, but the behavioral trait is sufficiently disclosed for a simple read tool.

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 concise (5 lines) and front-loaded with the main action. It is well-structured, with clear sentences explaining scope, metric definition, and interpretation legend. No extraneous information.

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 simple tool with no output schema, the description partially compensates by defining MOS and its interpretation, but it lacks exact output structure (e.g., format of the returned JSON). Given low complexity, it is somewhat incomplete.

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%, providing a baseline of 3. The tool description adds context by explaining the purpose of the IDs (voice call quality) and the output (MOS), but it does not enrich the parameter definition beyond what the schema already provides.

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 uses the specific verb 'Retrieves' and identifies the resource as 'voice call quality metrics for one or more conversations by ID'. It clearly distinguishes from sibling tools like conversation_sentiment and conversation_transcript by focusing on voice interactions and MOS scores.

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 does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. While the target use case (voice call quality) is implied by the name and explanation, no direct guidance is given about when not to use it or which sibling tool to choose instead.

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