Full QA pass with regression diff

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

With no annotations provided, the description carries the full burden of disclosure. It discloses the components included, the automatic comparison, the returned digest and diff buckets, and the policy constraint on mutating endpoints. It does not mention whether the run updates the stored baseline or the exact structure of the digest, but overall it provides solid transparency for a complex orchestration 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 and front-loaded, using two sentences to convey the core functionality and usage guidance. It avoids fluff, with every phrase earning its place—listing components, mentioning the diff, identifying the blocking bucket, and noting the policy constraint.

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 complexity (an orchestrator running multiple QA layers) and no output schema, the description adequately explains what the tool does and what it returns (digest plus diff buckets). It highlights the critical 'regressions' bucket but does not detail the full diff bucket structure or potential side effects (e.g., updating the stored run). This is a minor gap, but the description is largely complete for an agent to understand and invoke the 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?

The schema description coverage is 100%, so parameters (role, skipUi, maxPages, services) are fully documented in the schema. The description adds some context by mentioning the components (e.g., UI layers, API part), which aligns with skipUi and services, but it does not add new semantic meaning beyond what the schema already provides. This is the baseline for high schema coverage.

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 what the tool does: a complete QA pass covering discovery, generated API tests, YAML flows, Playwright specs, and frontend crawl, followed by a regression diff against the previous run. This is specific and distinguishes it from the sibling tools (which cover individual components like qa_discover, qa_run_api, etc.).

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 usage guidance, stating 'Use this as the release gate.' It also implies when to use the full run versus the individual sibling tools (e.g., qa_run_api or qa_run_flows), though it doesn't explicitly state when not to use it. The mention of 'regressions' as the blocking bucket further signals its role in release decisions.

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