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

Beyond annotations, the description details the two execution paths, the full verdict enum, and the critical semantics of 'could_not_verify' (not evidence) and 'unsupported' (no source covered). It also discloses the return payload (actual value, pipeworx:// citation, reasoning), which is not present in an output schema.

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?

Despite being longer than typical descriptions, every sentence contributes: trigger phrases, routing rules, verdict semantics, and caller warnings are cleanly separated with dashes and a bolded IMPORTANT. The structure is front-loaded with purpose and usage, making it easy to scan.

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?

With no output schema, the description fully covers return values (verdict types, actual value, citation, reasoning) and explains the two non-standard outcomes (could_not_verify, unsupported). It also addresses the multi-step alternative it replaces, making the tool comprehensible in context.

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 input schema already fully describes both parameters with 100% coverage. The description adds useful context by giving example claims and clarifying that tolerance_pct overrides the claim wording's implied tolerance, but this is supplementary rather than essential.

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 ('Is it true that…', 'fact check') and states the core function: natural-language claim verification against authoritative sources. It distinguishes this tool from siblings by explaining it replaces 4–6 sequential calls and handles both structured financial and general factual claims.

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 states 'Use whenever the agent needs to check whether something a user said is factually correct' and gives concrete routing rules (company-financial claims via SEC EDGAR, else grounded pipeline). It also tells callers when the tool is a shortcut by noting it replaces sequential NL parsing → entity resolution → data lookup → comparison.

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