QMetry: Fetch Builds

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral context beyond those annotations: it notes that an empty payload {} is sent when no parameters are provided, explains the output is a JSON object with pagination metadata, and clarifies filter behavior with example expected outputs.

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 front-loaded with a clear one-sentence purpose, but it becomes bloated: the parameter section duplicates the schema descriptions, the use cases list nine overlapping items, and the hints repeat defaults already present in the schema and examples. Several sentences do not add unique value, making the overall structure longer than necessary.

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 read-only fetch tool with no required parameters and no output schema, the description is largely complete: it explains the output shape, demonstrates all parameter behaviors through examples, and provides filter syntax. Minor gaps remain, such as not detailing the exact structure of the build objects returned, but overall the agent has enough context to invoke the tool correctly.

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 parameters are already documented structurally. The description goes beyond the schema by showing concrete filter JSON examples, naming common filter fields ('name', 'isArchived'), and explaining pagination defaults and behavior with expected outputs, which adds practical meaning an agent can use when constructing calls.

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 states a specific verb ('Fetch'), a concrete resource ('QMetry builds'), and a scoping qualifier ('from the current project'). It also adds the clarifying note that builds are known as 'drops', which further disambiguates the term and makes the tool identifiable among the many qmetry_ siblings.

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 a detailed 'Use Cases' section listing when to fetch builds, including for test execution planning, reporting, CI/CD integration, and filtered or paginated retrieval. It does not explicitly name alternatives to use instead, but the use cases give clear contextual guidance for when this tool is appropriate.

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