Rank by shape similarity

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description goes further by disclosing that no tier or causal label is produced ('the agent reads the flags and decides') and by explaining what each returned flag means, which is genuine behavioral context beyond the annotations.

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 text is dense and front-loaded with the core algorithm and workflow position, followed by a compact enumeration of output fields. Every sentence carries information, though the long inline field list is heavy for a single sentence and could be more scannable.

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 complex 12-parameter analysis tool, the description supplies the workflow framing, the semantic meaning of its outputs, and calibration caveats, and an output schema exists so return values need not be repeated. The remaining gap is input parameter coverage, which the description largely leaves to the 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?

With 12 parameters and only 42% schema description coverage, the description should compensate for undocumented parameters, but it does not. Parameters such as step, window, timeRange, environment, customer_metrics_auth and customer_metrics_type receive no explanation in either place, and the description's content is almost entirely about output fields rather than inputs.

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 names a specific operation (Pearson correlation + signed lag ranking) on a specific resource (a pre-filtered candidate set), and even states its position in the workflow ('Second step of cross-pillar investigation'). An agent can distinguish it from siblings like log10x_metric_overlay or log10x_metrics_that_moved without opening either schema.

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?

It clearly places the tool in a workflow, naming the typical input source ('the moved[] output of log10x_metrics_that_moved') and the composition partner ('Compose with log10x_metric_overlay for the final per-candidate aligned-timeseries view'). It does not state explicit exclusions or when-not-to-use, so it falls just short of a 5.

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