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

The description discloses substantial behavior beyond the readOnlyHint/openWorldHint annotations: exact match over 365 days, fallback 30-day substring scan, archive behavior for older sightings, defanged input handling, aggregated fields, and the explicit warning that returned AI-generated content is untrusted. This gives the agent a realistic model of what the tool does and what to expect.

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 front-loaded and information-dense, but it is structured as one sprawling multi-clause block with heavy parentheticals. Every detail is arguably useful, but the lack of bullet points or clearer segmentation makes it harder for an agent to parse quickly.

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 single-parameter enrichment tool with no output schema, the description is remarkably complete. It explains the lookup pipeline, exact-match aggregation, fallback behavior, archive results, domain-specific metadata conditions, campaign data, and the trust boundary for returned content. An agent has enough context to invoke it correctly and interpret the result shape.

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 one parameter with type auto-detection rules, so the baseline is 3. The description adds meaningful semantics beyond the schema by mentioning defanged input handling, http/https variants, and the distinction between exact and substring matching, which helps an agent know what value formats are acceptable.

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 opens with a specific verb and resource: 'Look up an IOC value in TweetFeed.' It goes well beyond the name by detailing exact lookup, fallback substring scanning, and enrichment content such as AI context, domain registration data, and campaign membership. This clearly distinguishes it from sibling tools like check_hash, check_ip, or check_url, even without naming them.

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 intended use case is implied rather than stated: an agent can infer this tool is for deep IOC enrichment, but the description never explicitly says when to choose it over sibling tools. There are no exclusions or alternative routing hints, so the agent is left to infer selection criteria from the observed feature richness.

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