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

Annotations already mark this read-only, idempotent, and non-destructive. The description adds genuinely useful behavioral context beyond those flags by disclosing the model assumptions: independent months, no costs, and that 'a real audit of the signals usually looks worse.' That is important for calibrating trust in the result.

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?

Three sentences front-load the main action, then the outputs, then the caveat. Every sentence earns its place and there is no repeated information from the schema or annotations.

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?

With no output schema, the description responsibly names the three return values and their interpretive meaning. It also includes the assumptions and limitations needed to use the result correctly; it only omits explicit guidance on when to escalate to the sibling audit tool.

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 description coverage is 100%, so all four parameters are already explained in the input schema; the baseline is therefore 3. The description's conceptual phrases like 'that many strategies' and 'edge of this size' map loosely to versionsTried and the return inputs, but they do not add details about the parameters beyond what the schema provides.

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 opens with a specific verb and object: 'Tests whether a trading strategy's claimed track record could be luck,' and it enumerates the three statistical outputs. It is clear on its own, but it does not explicitly contrast itself with the sibling explain_audit, so an agent must infer the boundary between a luck check and an audit.

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 final sentence provides an implicit usage context: this is 'a rough check' whose assumptions make results look better than a real audit. That implies use as a preliminary screen rather than a substitute for audit, but the description does not explicitly say when to choose luck_check over explain_audit or what conditions should route to the sibling.

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