Batch Job Duration Stats

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

The description discloses key behavioral traits: it fetches build history in parallel and computes statistics. Annotations already indicate readOnlyHint, idempotentHint, and non-destructive, so the description adds value by explaining the parallel execution and computation. It doesn't cover potential rate limits or data freshness, but given annotations, the additional context is strong.

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 and well-structured: a single sentence for the core purpose, a second sentence for behavioral detail, a third for usage context, and a bullet-like list of parameters. Every sentence is informative without redundancy. It is front-loaded with the essential purpose.

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 the tool's moderate complexity (4 params, 1 required) and the presence of an output schema, the description covers purpose, behavior, and parameter meanings adequately. It doesn't discuss error handling or output format, but the output schema presumably handles the latter. Overall, it provides sufficient context for an agent to select and 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?

Despite 0% schema description coverage, the description compensates fully by listing all four parameters with clear explanations: job_names (list of job names), tenant (optional default empty), result (filter by result, default SUCCESS for clean averages), and limit (builds per job, default 10, max 50). This adds significant meaning beyond the schema types alone.

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 tool's purpose: 'Get avg/min/max duration for multiple jobs in a single call.' It specifies the verb (get), resource (job durations), and scope (multiple jobs). It also distinguishes from siblings by noting it avoids making N separate API calls, which sets it apart from per-job tools like get_build_times.

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 explicitly states the intended use case: 'Designed for monitoring tools that need avg durations for an entire pipeline chain without making N separate API calls.' This provides clear context for when to use the tool. However, it does not explicitly mention when not to use it or list specific alternatives, missing a bit of guidance.

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