get_calibration_health_recommendations

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

No annotations are provided, so the description carries the full burden. It does disclose a meaningful constraint (requires Kiln Pro), but omits whether the call is read-only, what heuristics are used, how samples affect output, or what happens when insufficient data exists.

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 diluted by an upsell paragraph and a tracking URL ('?src=agent&tool=...') that consume more space than the functional content. The actual purpose sentence is front-loaded but thin, and the rest doesn't earn its place.

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 tool with no annotations and no output schema, the description should clarify return shape and behavior. Instead it leaves unclear what recommendations look like, whether they are applied or advisory, and how the sample threshold changes results.

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?

There is a single optional parameter with 100% schema coverage, so the baseline is 3. The description does not mention min_samples_per_category at all, so it adds no meaning beyond the schema.

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 phrase 'Recommend tunable noise floor + heuristic confidence levels' names a verb and somewhat specific subject, but it's unclear whether this returns calibration parameter suggestions, confidence-score classifications, or health advice, especially against sibling tools like classify_calibration_confidence and assess_calibration_status. Half the text is a Kiln Pro marketing pitch rather than functional clarification.

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 statement of when to call this versus assess_calibration_status, classify_calibration_confidence, apply_calibration_recommendations, or recommend_running_clearance. The only condition given is a paywall gate ('Requires Kiln Pro'), which is usage-relevant but not routing guidance.

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