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

The annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful context beyond those annotations by disclosing that results are cached for 5 minutes and by specifying which aggregate metrics are returned.

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?

Two short sentences with no wasted wording. The main purpose is front-loaded, and the caching note follows as a useful secondary detail.

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?

For a zero-parameter read-only stats tool with annotations covering safety semantics and an output schema defining the return shape, the description supplies everything needed: what is counted and how fresh the data is.

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 tool has zero parameters, so the baseline score is 4. There is no parameter meaning to clarify in the description.

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 resource being retrieved: aggregate counts of ideas analyzed and outcomes killed, fixed, or shipped. This is specific enough to distinguish a read-only stats lookup from the sibling judge_idea action.

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?

Usage is implied by describing aggregate statistics, but there is no explicit guidance on when to call this versus judge_idea or any other alternative. For a simple zero-parameter stats tool this is acceptable, though it leaves the agent to infer the use case.

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