Claim Support Check

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

Annotations already indicate readonly and idempotent behavior. Description adds rich behavioral context: case-insensitive keyword matching, per-page support threshold (≥50% keywords), aggregate verdict derivation, and 5-minute page caching. No contradictions.

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?

Description is a single paragraph that is clear and front-loaded with the core purpose. Could be slightly more concise in explaining the aggregation method, but no redundant sentences.

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 presence of an output schema and good annotations, the description covers all necessary behavioral aspects: purpose, matching logic, caching, and limitations. No gaps remain.

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%, but description adds value by explaining how keywords are matched (case-insensitive substring) and the aggregation rule (half of keywords per page), which is not obvious from schema alone.

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 uses a specific verb 'check' and resource 'factual claim supported by evidence URLs', clearly distinguishing from siblings like 'test_hypothesis' or 'search' by stating it's for evidence-backed checks on known pages, not open-ended 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?

Clearly states when to use (evidence-backed claims on known pages) and when not to use (not for open-ended search, semantic reasoning, contradiction extraction). Provides aggregate verdict logic but does not explicitly list alternative sibling tools.

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