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

Annotations already declare readOnlyHint=true and openWorldHint=false, covering the safety profile. The description adds real context beyond that: the method (unsupervised DBSCAN, CenDTect-style), an accuracy figure (AUC 0.65), and the fact that it surfaces 'shape-anomalous days labels never saw' — useful behavioral framing about output character and reliability.

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?

A single dense sentence that front-loads the core purpose and packs methodology, accuracy, and output character into a parenthetical. Every clause carries information, though the parenthetical is somewhat heavy for the tool's simplicity.

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 one-parameter read-only tool with no output schema, the description covers purpose, method, accuracy, and output character adequately. It lacks any note on return shape or usage conditions, but those are minor for a tool this simple.

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 single country_code parameter is fully documented in the schema (100% coverage, with ISO 3166-1 alpha-2 format examples), so the description adds nothing about parameter semantics. Baseline 3 is correct when the schema does all the work.

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 specific verb and resource (produces a DBSCAN anomaly score), scopes it explicitly to a country, and names its relative role as a 'second-opinion' that is 'weaker than the supervised classifier,' which corresponds to sibling tools like get_classifier_score. An agent can distinguish this from the supervised classifier tools without opening any 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?

The phrase 'second-opinion' implies when this tool is useful (as a complement to the supervised classifier), but the description never explicitly names an alternative or states a when/when-not condition. Usage is inferable but not spelled out.

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