Browse the fraud-cluster feed

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

Annotations already set readOnlyHint=true, covering the safety profile. The description adds a valuable data-quality caveat: 'Severity 'suspected' rows are publicly reported leads, not OilFlow-confirmed,' which helps the agent interpret results correctly.

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?

Three sentences, each earning its place: main action, use case, and a critical caveat. The primary operation is front-loaded, with no redundant wording.

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 list tool with no output schema, the description covers the feed source, filter options, and severity semantics. It does not mention pagination or return-field details, but those are not essential for a correct first invocation.

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 100%, with descriptions for all three parameters (since, country, severity). The description only restates the availability of these filters without adding format or constraint details 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 description clearly states a specific verb and resource: 'List entries from the Scam Cluster Intelligence Feed,' and identifies optional filters. While it does not explicitly contrast with sibling tools like cluster_check, the operation is unambiguous.

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 'Useful for browsing known fraud clusters' provides a clear context for when to call this tool. It does not name alternatives or exclusions, but the use case is sufficiently clear for a read-only feed-browsing operation.

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