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

Annotations already assert read-only, open-world, idempotent, and non-destructive behavior. The description adds substantial behavioral context beyond these: the special meaning of 'could_not_verify' (check did not happen, not evidence), the meaning of 'unsupported', the two verification pipelines, and the exact return contract of verdict/citation/reasoning. There is no contradiction with 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 long but every section adds value: trigger phrases, usage directive, routing logic, return value shape, and critical caller warnings. It is front-loaded with the most important identification information. It could be tightened slightly without losing nuance, but is well organized for a complex tool.

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 tool's complexity and the absence of an output schema, the description fully specifies the return contract: the six possible verdicts, the grounded/structured actual value, the pipeworx:// citation, and reasoning. It also clarifies error semantics (could_not_verify with verification_error) and unsupported results, so an agent would know exactly what to expect.

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 covers both parameters with full descriptions (100% coverage), including claim examples and the tolerance_pct default/cap. The tool description adds little parameter-specific semantics beyond mentioning percent-delta math, so with high schema coverage 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 opens with recognizable fact-check trigger phrases and explicitly defines the tool as 'natural-language claim verification against authoritative sources,' with a specific outcome (verdicts such as confirmed/refuted). This clearly distinguishes it from general-purpose sibling tools like ask_pipeworx_grounded or deep_research by focusing on judging factual truth rather than answering open-ended questions.

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 when to use it: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also gives internal routing rules for financial vs. non-financial claims. However, it does not name alternative tools or provide explicit 'do not use when' conditions, so it misses the threshold for a 5.

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