athena_decision_evsi

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

No annotations are provided, and the description discloses no behavioral traits—no side effects, state changes, prerequisites, or computational implications. 'DESIGN_ONLY' is ambiguous and does not meaningfully inform the agent about what happens when the tool is invoked.

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 one sentence, but its extreme brevity is under-specification rather than effective conciseness. Given the technical complexity, it should include more context while still being direct.

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?

This is a specialized statistical tool with no annotations, no output schema, and a single cryptic sentence. It lacks essential information about inputs, expected outputs, or usage context, making it inadequate for an agent to use correctly.

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 description mentions none of the seven parameters. With 0% schema description coverage, the agent is left to guess the meaning of 'context_key', 'actions', 'experiments', 'cost_weight', 'risk_weight', 'seed', and 'samples'. The description provides no value beyond the parameter names.

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 operation: estimating expected value of sample information (EVSI) for finite Gaussian linear experiment designs. The phrase 'finite Gaussian linear experiment designs' differentiates it from related decision-analysis tools like athena_decision_evi and athena_decision_evpi, though it does not explicitly name these siblings.

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?

No guidance is provided on when to use this tool versus alternatives. 'DESIGN_ONLY' is a terse label that hints at scope but does not clarify conditions or alternatives, leaving the agent without decision criteria.

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