QMetry: Fetch Issue Details

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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so no side-effect disclosure is needed. The description adds useful behavioral context beyond annotations: response contains a UDFTypeData map, the defectId must come from the list response's 'id' field, and entity keys require a pre-fetch step. There is no contradiction with the annotations.

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 well-structured with clear sections: summary, parameters, output, use cases, examples, and hints. It is longer than necessary because the Parameters section mostly repeats input schema descriptions, but the additional examples and workflow guidance are valuable. No critical content is missing, though minor redundancy prevents a perfect score.

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 there is no output schema, the description compensates well by stating that the response is a JSON object with a 'data' property containing full issue details and the UDFTypeData map. It also explains how to obtain the required defectId, provides expected outputs, and gives a complete workflow for fetching UDF values. This is sufficient for a moderately complex read-only 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 100%, so the baseline is 3. The description goes beyond the schema by warning not to derive defectId from the entity key suffix and by describing an AUTO-RESOLVE flow when a user supplies an entity key instead of a numeric ID. The examples also reinforce the expected parameter usage.

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 a specific verb ('Fetch') plus a concrete resource ('full detail data for a QMetry issue including UDF field values'), which clearly distinguishes this tool from list-oriented siblings like qmetry_fetch_defects_or_issues. It also states the output focus on UDFTypeData and custom fields, making the tool's purpose unmistakable.

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 provides explicit 'Use Cases' and a detailed 'Workflow' explaining exactly when to call this tool, including how to resolve an entity key via Fetch Issues/Defects first. It does not explicitly name excluded alternatives or say 'do not use this for listing issues', but the context is clear enough for correct selection.

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