get_health_metrics

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

The description adds substantial behavioral context beyond annotations: it reveals the `coverage` block with real firstDate/lastDate/days, warns to verify long windows, clarifies that `aggregate` is computed over the full range even when points are rolled up, and mentions segmentBoundaries for point events. These are meaningful nuances that annotations (readOnly, idempotent) do not cover.

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?

Only three sentences: purpose first, then critical behavioral warnings, and a final note about segmentBoundaries. Every sentence contributes value, and the most important caveats are front-loaded after the core purpose.

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 complexity (7 params, nested object, no output schema), the description covers essential pitfalls: the coverage block, aggregate behavior with rollups, and event segments. It explains partial return structure but leaves some details (error behavior, exact format of points) to inference. Still, it is reasonably complete for a read-only tool without an output schema.

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 coverage is 86%, so most parameters already have descriptions. The tool description does not add per-parameter semantics beyond the schema; it focuses on general behavior and result structure. The baseline of 3 applies since the schema handles the heavy lifting, and the description's behavioral notes (e.g., aggregate over full range) are more about operation than parameter meaning.

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 states a precise verb and resource ('Get values for a metric (or all metrics) over an optional date range, with an aggregate') and even labels itself 'The core data-retrieval tool,' which conveys its role. However, it does not explicitly differentiate from siblings like get_trends or compare_periods, leaving potential ambiguity about which tool covers which analytical task.

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?

Calling itself 'the core data-retrieval tool' implies it is the general-purpose retrieval endpoint, but there is no explicit guidance on when to prefer siblings, what user scenarios warrant get_trends vs. this, or exclusions. The guidance is implied rather than stated.

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