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

This is exemplary. The description discloses the two backend paths, the exact verdict enum, and the meaning of each result, especially the critical distinction between 'could_not_verify' (check did not happen) and 'unsupported' (no source exists). It also warns callers not to treat 'could_not_verify' as evidence for or against the claim. This goes far beyond the annotations, which already indicate a safe, read-only, idempotent operation.

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, it is well-structured and front-loaded: starting with natural-language triggers, then routing logic, return values, caller warnings, and an efficiency note. Every sentence adds value, and the density is appropriate for a tool with this complexity. The mention that it 'replaces 4–6 sequential calls' is a useful, non-redundant addition.

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 that there is no output schema, the description fully covers the return structure (verdict enum, actual value, citation, reasoning) and clarifies edge cases. It also provides enough context about the two processing pipelines and tolerance behavior. An agent can confidently select and invoke this tool based on the description alone.

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 thorough descriptions for both parameters, including examples for 'claim' and detailed override semantics for 'tolerance_pct' (range, default, use cases). The description itself adds no new parameter-specific information, so with 100% 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 clearly states the tool's purpose: natural-language claim verification against authoritative sources, with examples like 'fact check' and 'verify the claim that…'. It goes beyond a simple definition by describing the two processing paths (SEC EDGAR for financial claims, grounded pipeline for others) and the verdict-based output, which distinguishes it from general Q&A tools like ask_pipeworx.

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 explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct,' providing a clear invocation trigger. It also explains the routing logic for financial vs. non-financial claims, which helps the agent decide when to use it. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a 5 on this dimension.

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