Step 2: validate the data against the test's assumptions

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

Annotations cover the safety profile (readOnlyHint=true, destructiveHint=false), and the description adds real content beyond them by enumerating exactly which assumptions are tested, so the agent knows the scope of the check. It doesn't describe the failure signal or response shape, and the idempotentHint=false is left unexplained for what looks like a pure read.

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 tight sentences, with the step number front-loaded so the agent immediately places it in the sequence, followed by the concrete check list and the remediation pointer. No filler and nothing redundant with the schema.

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 parameters and no output schema, the description is nearly complete: it says what is validated and what to do if validation fails. The remaining gap is the return shape — an agent can't tell whether it gets per-assumption pass/fail flags, statistics, or a single verdict — but everything needed to decide to call it is present.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline applies. The description correctly implies all inputs come from prior workflow state rather than arguments.

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?

States a specific verb ('Checks') and an enumerated set of resources: shape (skew, kurtosis, small samples), group sizes, outliers, expected counts, ANCOVA slope equality, missing values. It anchors itself in the workflow ('for the test fixed in step 1'), which clearly separates it from siblings like choose_test, state_hypotheses and run_test.

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 positions the tool as step 2, downstream of step 1's test selection, so the 'when' is unambiguous. It also routes the agent on failure conditions by naming the alternative — 'revising the test now (state_hypotheses again) is principled' — though it doesn't state the prerequisite that a test must already be fixed or what to do on a pass.

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