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

The description adds substantial behavioral context beyond the annotations: it explains the two pipeline paths (SEC EDGAR + XBRL and grounded), the list of possible verdicts, the meaning of 'could_not_verify' versus 'unsupported,' and the verification_error structure. This is consistent with the read-only, open-world, idempotent annotations and enriches the agent's understanding of the tool's behavior.

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 lengthy but every sentence carries meaning—starting with natural-language trigger examples, then usage guidance, then pipeline routing, then return values and error semantics. It is front-loaded with examples and efficiently structured, though slightly dense.

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?

Despite lacking an output schema, the description fully explains what the tool returns (verdict, actual value with pipeworx:// citation, reasoning), the special meanings of particular verdicts, and the failure semantics. It also notes the efficiency benefit over multiple sequential calls, making it self-sufficient for an agent.

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 provides 100% coverage with detailed descriptions for both 'claim' and 'tolerance_pct,' including examples and constraints. The tool description does not need to add parameter semantics, and it doesn't; it focuses on the overall behavior, which is acceptable given the high schema coverage.

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 performs natural-language claim verification against authoritative sources, with specific verbs like 'verify,' 'fact check,' and 'confirm or refute.' It also distinguishes itself from sibling tools by explicitly covering both structured SEC EDGAR/XBRL financial claims and a grounded pipeline for any other factual claim.

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,' providing clear context for when to invoke it. It also explains the routing for financial vs. non-financial claims, but it does not explicitly name alternative tools for non-claim research or state when not to use it.

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