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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description goes far beyond this by revealing two internal pipelines (SEC EDGAR+ XBRL fast path vs grounded pipeline), the exact verdict vocabulary, and the critical distinction that 'could_not_verify' means the check did not happen and must not be treated as evidence. This is substantial behavioral context that annotations cannot convey.

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?

Although the description is long, it is structured with an opening line of trigger phrases, a clear 'Use whenever' directive, a breakdown of claim types and pipelines, and a clearly marked 'IMPORTANT for callers' caveat. Each sentence conveys non-redundant, meaningful information. The front-loading of trigger phrases and the crucial error-handling note are placed appropriately.

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?

The tool has no output schema, so the description must explain return values itself. It does so by listing the verdict set, the actual value with citation, and reasoning. It also explains error and edge-case semantics ('could_not_verify' vs 'unsupported') and provides a fallback routing explanation. For a tool with this complexity, the description is remarkably 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?

Schema coverage is 100% with good descriptions for both parameters. The tool description adds extra meaning by explaining that tolerance_pct can override the tolerance implied by claim wording and is useful for hallucination detection. It also gives concrete claim examples that help ground the 'claim' parameter. This goes beyond the schema's baseline, so a 4 is warranted.

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 starts with natural-language trigger phrases ('fact check', 'verify the claim that...'), then states the exact function: natural-language claim verification against authoritative sources. It clearly distinguishes itself from sibling tools by describing the specific job of verifying user claims and even mentions replacing multiple sequential calls, which positions it uniquely among the listed sibling tools.

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 explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and further differentiates the handling of company-financial claims vs any other factual claim. It does not explicitly name alternative tools to avoid or exclusions (e.g., 'do not use for opinions'), which prevents a 5, but the guidance is clear and practical.

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