Flaky Job Detection

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context by explaining the analysis methodology (computes pass/fail statistics, threshold for flaky) and parameter behaviors like limit max and tenant default, which goes beyond the structured 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 a clear one-sentence summary, a brief paragraph on the detection logic, and a numbered Args list. It is a bit verbose due to the parameter details, but every sentence serves a purpose and is easy to scan.

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 that the tool has an output schema, the description does not need to explain return values. It covers the purpose, methodology, all input parameters with semantics, and acknowledges defaults/limits. It does not list prerequisites or when not to use, but for a read-only analysis tool, it is sufficiently complete.

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%, and the description fully compensates by providing meaningful explanations for each parameter: job_name, tenant, project, pipeline, limit, and detail. It clarifies defaults, filters, and what the detail flag does, adding value beyond the raw schema.

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: 'Detect flaky jobs by analyzing recent build history for intermittent failures.' It uses a specific verb ('detect') and resource ('flaky jobs'), and the method is described. This distinguishes it from sibling tools like get_job or get_build.

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 explains what the tool does and even provides a criterion (>20% failure rate), but it does not explicitly state when to use this tool over alternatives or mention any exclusions. Usage is implied rather than directly contrasted with siblings.

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