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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real value beyond that: it discloses the method is unsupervised/DBSCAN, that output carries 'model caveats,' and that results are exploratory ('may surface') rather than authoritative. It stops short of describing the return shape or any rate/limit behavior.

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?

Two dense sentences, front-loaded with what the tool produces before the caveat about complementary coverage. 'CenDTect-style' is unexplained jargon, but nothing is padded.

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 read-only, single-param tool with no output schema, the description is close to sufficient, but it leaves ambiguity about the result shape — a scalar country-level score versus a per-day anomaly list — which matters given the phrase 'surface shape-anomalous days.' A brief note on the returned granularity would close the gap.

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% for the single country_code parameter, and the schema already documents the ISO 3166-1 alpha-2 format with examples. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 gives a specific verb (read/score), resource (anomaly score for a country) and method (unsupervised DBSCAN, CenDTect-style). It distinguishes itself from the supervised-label path by framing itself as a 'second opinion,' though it names no sibling tool explicitly.

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 implies usage via 'second-opinion' and 'may surface shape-anomalous days the supervised labels missed,' which hints at when to reach for it over a supervised classifier. However, it never states an explicit when-to-use/when-not condition or names the alternative tool (e.g., get_classifier_score) to route the agent.

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