fact-check

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

With no annotations provided, the description fully discloses behavior: parallel search across four sources, use of GPT-4o-mini for assessment, structured verdict with confidence score, evidence excerpts, source URLs, entities, and step-by-step reasoning. Cost is also mentioned ($0.150/call), which is valuable for decision-making.

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 compact (3-4 sentences) and well-structured: purpose first, then method and output, then usage context, finally cost. Every sentence adds value without redundancy.

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?

The description explains the return type (verdict, confidence, evidence, etc.) and overall behavior. Without an output schema, this is sufficient. However, it could be slightly more detailed about how evidence excerpts are selected or whether sources are always included. Still, it is largely complete for the tool's complexity.

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 coverage is 100%, and the description adds meaningful guidance beyond the schema: for the 'claim' parameter, it advises specificity ('vague claims return uncertain verdicts') and for 'context', it explains how it 'narrows the verification scope'. This helps the agent use parameters effectively.

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 'AI-powered claim verification' with specific sources (DuckDuckGo, Wikipedia, Hacker News, arXiv) and returns a structured verdict. It distinguishes well from sibling tools like research-paper-search or hn-search by focusing on fact-checking rather than raw search.

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 advises using the tool 'before an agent acts on a factual assertion it received from another agent or user', which gives clear context. However, it doesn't explicitly mention when not to use it (e.g., subjective opinions) or provide direct alternatives among siblings.

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