get_recommendations

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions regeneration capability via ?force=true (though undocumented) and implies a read operation. It does not discuss side effects, rate limits, or error states. The dependency on prior sync is disclosed, but the behavior around performance metrics and AI landscape changes is not detailed.

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 consists of three concise sentences, front-loaded with the core purpose. Each sentence adds essential information: what it does, what it returns, and prerequisites. There is no fluff 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?

Given the complexity (2 parameters, no output schema), the description covers key aspects: inputs, outputs, prerequisite, and regeneration capability. It provides sufficient context for an AI agent to decide when to invoke this tool versus siblings like sync_implementation_state. The lack of output schema is partially compensated by the mention of 'prioritized, actionable recommendations.'

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% (both parameters have descriptions), so baseline is 3. The description adds no value for the defined parameters (blueprintId, customerOrgId) and instead introduces a non-existent parameter 'force' via ?force=true, which could mislead an AI agent. This inconsistency reduces the score below baseline.

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 gets strategic recommendations for a blueprint, specifying the inputs (implementation state, performance metrics, AI landscape changes) and output (prioritized actionable recommendations). It distinguishes from siblings by mentioning the prerequisite sync_implementation_state, but does not explicitly compare to other get tools. The verb 'get' combined with 'recommendations' is specific and unambiguous.

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 explicitly states a prerequisite: 'Requires implementation state to be synced first via sync_implementation_state.' This guides when to use the tool. However, it also mentions '?force=true to regenerate' which implies a parameter not present in the input schema, creating confusion. There is no guidance on when not to use or alternatives to other tools.

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