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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds substantial behavioral detail beyond this: the two routing paths (SEC EDGAR vs. grounded), the exact verdict values, the critical semantics of could_not_verify (not evidence, carries verification_error) and unsupported, and the pipeworx:// citation. This gives the agent a clear model of what the tool does and how to interpret results, with no contradiction to annotations.

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 longer than average but each segment serves a purpose: trigger phrases, purpose, usage, pipeline routing, return values, and a caller warning. It is front-loaded with the most important information. It is slightly verbose with some redundancy (e.g., listing many trigger phrases), but overall well-structured and not wasteful.

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 covers the necessary aspects: the verdict set with semantics, the two pipeline behaviors, the error case (could_not_verify) with its structured error, and the fact that it collapses multiple sequential calls. The combination of annotations, schema, and description gives the agent a full picture of how to invoke and interpret the tool.

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 description coverage is 100%, and both parameters (claim, tolerance_pct) already have rich descriptions in the schema, including defaults, ranges, and usage examples. The tool description itself does not add parameter-level details, but since the schema does the heavy lifting, a baseline score of 3 is appropriate.

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's purpose as natural-language claim verification against authoritative sources, with explicit trigger phrases ('fact check', 'verify the claim that...') and a specific resource. It also distinguishes between two verification pipelines (structured SEC EDGAR/XBRL for company-financial claims vs. grounded pipeline for other claims), setting it apart from sibling tools like ask_pipeworx or deep_research.

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 gives explicit usage guidance: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also notes that it replaces 4–6 sequential calls, indicating when to prefer this composite tool. However, it does not explicitly name alternative tools or discuss when not to use it, so a small gap remains.

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