anova

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

With no annotations provided, the description carries the full behavioral burden. It does add genuine value by disclosing that '@<path>' file references are NOT supported for groups (a constraint the schema does not express) and by listing the returned statistics, but it says nothing about assumptions, error behavior, or the shape of the result payload.

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 paragraphs, front-loaded with the operation and its returns, with the parameter constraint called out separately. No filler, though the '@path' note could be tightened.

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 single-parameter statistical test with no output schema, the description covers inputs and returns adequately but omits the assumptions and alternative-selection context an agent needs to call the right test. It is viable but leaves clear gaps.

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 0% — the schema only supplies a bare title 'Groups' — so the description must compensate, and it does: it explains that groups is a nested list of samples and explicitly rules out '@<path>' file references, which is exactly the kind of constraint an agent would otherwise guess wrong.

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+resource ('Run a one-way ANOVA') and even names the returned statistics (F statistic, p value, degrees of freedom), so the operation is unambiguous. It does not, however, differentiate itself from near siblings such as t_test or chi2_test, which is the only thing keeping it from a 5.

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?

There is no when-to-use guidance at all — nothing tells the agent to prefer this over t_test when comparing more than two group means, or what assumptions (normality, homoscedasticity) apply. The usage is only implied by the tool name.

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