Full health verdict + four signals for one release

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

With no annotations, the description carries the full burden. It discloses that the health is pre-computed, returns deltas, and includes critical warnings about null handling and authoritative fields. This provides sufficient behavioral context beyond the schema.

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 a single sentence but packs all key information: what is returned, the authoritative fields, and null handling. It is front-loaded with the main purpose. Could be slightly improved with bullet points, but overall concise.

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 no output schema, the description covers the main return values (health verdict, four signals, code context, delta) and includes important caveats about conversion_rate. It is sufficiently complete for an agent to understand what to expect.

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 input schema already has 100% description coverage for all three parameters, including types, defaults, and ranges. The description adds no additional parameter semantics beyond what's in the schema, so baseline 3 is appropriate.

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 explicitly states it returns the full pre-computed health verdict, all four signals, code context, and delta for ONE release. This clearly differentiates it from sibling tools like release_list or release_regressions, which have different purposes.

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 guidance on how to use the outputs: health_status and health_score are authoritative, and not to derive verdicts from individual rates. It also warns that conversion_rate may be null. However, it does not explicitly compare to alternatives like release_regressions for when to use this tool.

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