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

Despite no annotations, the description discloses key behavioral traits: case-insensitive substring match, 30-day time window, returned fields (date, researcher, value, tags, source URL), and a security warning about treating community data as data not instructions. This fully informs the agent of expected 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?

The description is concise with four focused sentences, no redundant information, and a clear structure: action, use case, behavior, output, and caution. Every sentence adds value.

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 a single parameter, no output schema, and no annotations, the description completely covers what an agent needs to use the tool correctly: what it does, how it matches, time frame, output fields, and a security note. No gaps remain.

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 a well-described parameter. The description adds value beyond the schema by explaining the search scope (substring, case-insensitive) and the 30-day window, providing richer semantic meaning.

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 the tool checks whether a URL appears in the TweetFeed corpus over the past 30 days. It specifies the action, resource, and time window, and is easily distinguishable from sibling tools like check_hash and check_ip which check other IOC types.

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 provides clear context for when to use the tool: 'confirming if an observed URL has been flagged by the public infosec Twitter/X community.' It does not explicitly exclude alternative tools or provide when-not-to-use guidance, but the context is sufficient for typical use.

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