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

Beyond the annotations, the description discloses two routing paths (SEC EDGAR fast path vs. grounded pipeline), the nuanced meaning of could_not_verify vs. unsupported, and the existence of verification_error{stage,detail}. It also explains the tolerance override semantics. These are behavioral details far beyond what annotations alone provide.

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 dense but every sentence earns its place: trigger phrases, routing logic, output contract, error caveats, and efficiency benefit. It is well-structured as a single coherent block, front-loaded with the most actionable information, and avoids redundancy.

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 complex tool with no output schema, the description fully explains the return values (verdict, actual value, citation, reasoning), the special meanings of could_not_verify and unsupported, and the two pipeline paths. It gives the agent all necessary operational context to invoke the tool correctly and interpret results.

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?

Both parameters have descriptive types in the schema, so baseline is 3. The description adds meaningful usage context for tolerance_pct (e.g., set 1–2 for hallucination detection, default implied by wording capped at 5) and clarifies the claim parameter's scope with examples. This goes beyond the schema's simple field descriptions.

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 explicit trigger phrases like "fact check" and "verify the claim that…" and states a specific verb+resource: natural-language claim verification against authoritative sources. It clearly distinguishes itself from sibling tools by describing a composite, high-level operation that replaces 4–6 sequential calls, making its scope unmistakable.

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?

It explicitly says "Use whenever the agent needs to check whether something a user said is factually correct," which is clear when-to-use guidance. It also differentiates handling for company-financial claims vs. other claims, but it does not mention exclusions or alternatives (e.g., when to use ask_pipeworx instead), so it misses the full 'when-not/alternatives' bar.

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