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

Beyond the idempotentHint annotation, the description adds the prerequisite of OAuth or API key with the approve scope and clarifies the post-condition, enhancing transparency without contradicting 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 brief and to the point, with three succinct sentences covering purpose, usage condition, effect, and requirement. No unnecessary words or repetition.

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?

It includes the prerequisite, effect, and usage condition, which is sufficient for a simple rejection operation. Output details are not covered, but since an output schema exists (as indicated in context signals), this is acceptable.

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 only parameter, changeSetId, is not described in either the schema (which provides only type and format, no description) or the tool description. The name is self-explanatory, but the description does not explicitly compensate for the lack of schema description, leaving some ambiguity.

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 function: 'Close one drafted change set without approving it.' This is specific and distinguishes it from sibling tools like approve_change.

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?

It provides a usage condition ('Call this only when the customer says so') and explains the effect ('The job stays proposed and can be drafted again later'), but does not explicitly compare with alternative tools like approve_change.

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