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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses important behavioral nuances: it explains that `could_not_verify` means the check did not happen and must not be interpreted as evidence, and that `unsupported` means no source was covered. It also reveals the two internal pipelines (structured vs. grounded) and that the tool replaces 4–6 sequential calls. These details materially enhance the caller's understanding of what the tool does and how to interpret its results.

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 appropriately sized for a tool of this complexity, with a clear structure: examples first, then usage, routing logic, return values, and critical caveats. Every sentence adds value—there is no filler or repetition. It is front-loaded with natural-language examples that immediately convey intended use.

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 the lack of an output schema, the description fully explains the return value structure (verdict enum, actual value with citation, reasoning) and explains edge-case verdicts (`could_not_verify`, `unsupported`). It also covers the tool's behavior across different claim types and the routing to structured vs. grounded pipelines. This is complete for an agent to invoke the tool correctly and interpret results without additional 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 has 100% coverage with detailed descriptions for both `claim` and `tolerance_pct`, including examples and default behavior. The main tool description, however, does not add any additional parameter semantics beyond what the schema already provides. Since schema coverage is complete, the 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: natural-language claim verification against authoritative sources, returning a verdict. It uses specific verbs like "verify" and "fact check" and explicitly describes the output (verdict, actual value, reasoning). This distinguishes it from siblings like ask_pipeworx_grounded, which is a general grounded Q&A tool, whereas validate_claim is narrowly focused on validating factual claims with a structured verdict.

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 provides explicit usage guidance: "Use whenever the agent needs to check whether something a user said is factually correct." It also details two distinct routing paths (SEC EDGAR for company-financial claims, grounded pipeline for others), which helps callers understand when this tool applies. However, it does not explicitly name alternative tools to use instead or mention when not to use it, so it stops short of a 5.

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