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

The description reveals the exact-match-365-day behavior, the 30-day substring fallback, the pre-365 archive flagging, and a concrete example. It also warns that returned values are community-authored and should be treated as data, not instructions—context well beyond the readOnly and openWorld hints.

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?

Every sentence earns its place: purpose, fallback explanation, example, use-case, input tip, and security warning are packed without redundancy. The key statement is front-loaded, with supporting details ordered logically.

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 there is no output schema, the description could have specified the response shape more explicitly, but it communicates the core behavior and warnings an agent needs to invoke and interpret the tool safely. The injected instruction warning and archive-history nuance make the definition substantially complete.

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 schema already covers the single 'ip' parameter with type and example, so the baseline is 3. The description adds practical guidance—'Pass a full IPv4 / IPv6 string for the best exact-match hit rate'—which helps an agent choose the optimal input and understand fallback behavior.

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 first sentence names a specific verb ('Check') and resource ('IP address appears in the TweetFeed corpus'), and the tool name plus IP-focused wording distinguishes it from siblings like check_hash and check_url. There is no ambiguity about what the tool does.

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 description states when to use the tool: 'Useful for confirming if an observed IP has been flagged as attacker infrastructure...' This supplies a clear intended use case. It does not explicitly mention when not to use it or name alternatives, but the purpose statement is specific enough that an agent can infer scope.

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