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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds that it returns structure, when-to-use, pitfalls, and examples, which provides some output context but not much beyond annotations. No contradictions.

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 at two sentences, front-loaded with the core purpose. Every sentence adds value—the first lists contents, the second gives usage triggers. No wasted words.

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 simple tool with only two params, no output schema, and rich annotations, the description is complete. It tells the user what they get (structure, when-to-use, pitfalls, examples) and when to use it, which is sufficient for this scope.

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 'id' and 'search' fully described in the schema. The description does not add any additional meaning beyond what the schema already provides, so the 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 clearly states the tool retrieves product-metrics frameworks and lists the specific frameworks (HEART, AARRR, etc.), which distinguishes it from siblings like get_business_strategy or get_checklist. The verb 'get' plus resource 'product-metrics framework' is specific, and the usage intent is clearly conveyed.

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?

Explicitly states when to use: 'Use when the user asks how should we measure success? or what metrics should we track?' This is clear context. It does not mention when not to use or alternatives, so it falls short of a 5 but is still strong.

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