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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description reinforces these ('Every call is read-only and idempotent') and crucially adds error handling behavior: 'never raises a protocol error — it returns {"error": ...}' with a concrete example. This goes beyond annotations and provides essential safety knowledge.

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 dense but not wasteful: one sentence for purpose, one example block, one usage guideline, one error note, and one safety reassurance. Every sentence earns its place, and the structure is front-loaded with the core action.

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 the tool's moderate complexity, the description covers the full picture: purpose, assumptions, alternative tool, error behavior, idempotency, and a worked example. The presence of an output schema reduces the need to detail return values, and the description compensates fully for any remaining 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 100%, so the schema already describes each parameter. The description adds value with a concrete example ('mean:72.4, std_dev:8.1, n:64, confidence_pct:95') that shows how inputs combine to produce outputs, plus error constraints ('confidence 90/95/99, n>=2, std_dev>=0') that reinforce schema rules. This extra context merits a 4 rather than the baseline 3.

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 'Compute a confidence interval for a mean (normal approximation)', specifying the exact verb and resource. The example input and output further clarify what the tool does, and the sibling tools (e.g., sample_size, stats_describe, ab_test) are distinct, so no confusion arises.

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?

Explicit guidance: 'Use on data already collected, for a mean' and 'Not for proportions or two-group comparisons - the data server's ab_test compares two proportions.' It also warns about unreliability on very small or heavily skewed samples, giving clear when-to-use and when-not-to-use context with an alternative tool.

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