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

Annotations cover the safety profile (destructiveHint=false, openWorldHint=true), so the description's burden is lighter. It adds interpretive behavior ('not admission to anything and is not a forecast') and clarifies which inputs drive which outputs. It does not state that the call is a pure stateless computation or whether anything is persisted, which matters given readOnlyHint=false.

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 sentences, front-loaded with the method and citation, no filler. The second sentence packs two distinct ideas (sibling routing and threshold caveat) and is grammatically dense, but every clause carries information.

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?

An output schema exists, so return values need not be explained; the description still covers method provenance, the routing alternative, and a misuse caveat. It leaves open how this differs operationally from related siblings like validate_luck_trials and validate_overfitting, which is the main remaining gap.

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 the schema already documents all six parameters including worked examples (252 daily, 365 crypto). The description only loosely links inputs to outputs ('by Bonferroni and independent tests', 'with the other tests' Sharpes, Holm and BHY'), which is baseline-level added value.

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?

Names a specific computation (haircut Sharpe for multiple testing, Harvey and Liu 2015) and enumerates exactly what it returns: Bonferroni/independent-test haircuts and Holm/BHY adjustments. It also names the sibling it is not (validate_deflated_sharpe), so an agent can route without opening the schema.

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?

Gives one explicit routing rule: 'For the probability the Sharpe is real, use validate_deflated_sharpe.' That is a real alternative-plus-condition. It does not cover when to prefer this over other siblings such as validate_overfitting or validate_luck_trials, so it stops short of full when/when-not guidance.

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