approve_recommendation

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

With no annotations provided, the description carries full burden. It discloses key behaviors: executing exactly one recommendation, safety guardrails (blast-radius caps, rate limits, auto-rollback), and non-interference with other pending recommendations. This is strong for a mutation tool, though it does not mention return values or error handling.

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 two sentences, directly stating the action and then the safety constraints. No filler or repetition; every clause adds meaningful information. It is well-structured for quick parsing.

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 simplicity (2 required string params, no output schema, no nested objects), the description covers purpose, scope, safety features, and effect on other recommendations. It could mention the return value, but overall it is sufficiently complete for an agent to invoke 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?

Schema coverage is 100% with both parameters described as 'from list_recommendations', making the parameters self-explanatory. The description adds minimal semantic value beyond 'ONE' and 'already-diagnosed', which slightly reinforces the schema but does not compensate for any gaps. Baseline of 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 uses specific verb 'Approve and execute' and specifies the resource as 'ONE already-diagnosed optimization recommendation', clearly distinguishing it from sibling tools like list_recommendations or check_approval. It conveys the exact action and scope without ambiguity.

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 establishes clear usage context: it is for approving and executing an already-diagnosed recommendation, with safety guardrails. It also clarifies that other pending recommendations remain untouched, which hints at when this tool is appropriate. It does not explicitly name alternatives, but the context strongly implies its niche.

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