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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds critical behavioral detail: the SEC EDGAR fast path, the fallthrough to the grounded pipeline with verbatim evidence, and the crucial caller warning that 'could_not_verify means the check did not happen... it is NOT evidence for or against the claim.' This significantly goes beyond what annotations 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?

Though long (~200 words), it is well-structured and dense: trigger phrases, core use case, claim-type routing, verdict list, caller warning, and efficiency note. Every sentence carries information, and it is front-loaded with the purpose and trigger examples. No redundancy or filler.

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?

Given there is no output schema, the description fully specifies return values (verdict enums, actual value with citation, reasoning) and explains failure modes (could_not_verify vs unsupported). It also covers the distinction between financial and non-financial claims, making it complete for a complex verification 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 covers both parameters with helpful descriptions, but the description adds practical value: for tolerance_pct it explains 'set 1–2 for hallucination detection where any material error must be refuted,' and for claim it gives concrete examples. This enriches the schema and guides correct parameter usage.

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 trigger phrases and states 'natural-language claim verification against authoritative sources.' It clearly differentiates from siblings like ask_pipeworx_grounded by focusing on claim verification and explicitly says it 'Replaces 4–6 sequential calls,' positioning it as the dedicated fact-checking tool.

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.' It also distinguishes between company-financial claims and all other factual claims, explaining the routing to SEC EDGAR vs the grounded pipeline. This gives clear guidance on when to invoke and what to expect, beyond generic alternatives.

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