athena_interaction_higher_order

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

No annotations are present, so the description must carry the transparency burden. It discloses the important limitation that missing cells remain UNIDENTIFIED, but does not state whether the operation is read-only, whether it has side effects, or any permission requirements. The verb 'Compute' hints at a non-mutating operation but is not explicit.

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?

The description is concise, with two sentences that both add value: the first states the core function, and the second provides a critical caveat. It could be slightly more structured, but there is minimal waste.

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?

Given no output schema and no annotations, the description is not complete enough for autonomous use. It lacks details on return values, how to interpret contrasts, and the role of design_confidence. The missing-cell warning helps but does not compensate for the overall lack of context.

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?

With 0% schema description coverage, the description must compensate for parameter meaning. It loosely maps 'order-2..4' to max_order and 'Every 2^k cell' to experiments, but design_confidence is entirely unexplained. The mapping to experiments is also indirect and not clear enough for an agent.

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 tool computes 'order-2..4 factorial inclusion-exclusion contrasts', a specific statistical operation. It also provides a key distinguishing constraint ('Every 2^k cell is required'), but does not explicitly contrast with sibling tools like athena_interaction_credit.

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 description implies when to use the tool by requiring a full 2^k factorial design and warns that missing cells lead to UNIDENTIFIED results. This serves as a practical precondition but stops short of naming alternatives or explicitly stating when not to use it.

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