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

The description adds significant behavioral context beyond the annotations (readOnlyHint, destructiveHint): it explains match types (exact, case-insensitive or normalized), the possible verdicts (matches_record, matches_quote, differs, not_found), and that it returns the source URL and quote. This is more than what annotations provide. 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 a single paragraph but is concise and front-loaded with the key question 'Is this value actually right?' Every sentence earns its place: purpose, reporting details, usage guidance, and verdicts. It is not overly long, though it could be more structured (e.g., bullet points for verdicts) to improve scanability.

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 has 4 parameters and no output schema, the description adequately covers the main outputs (verdicts, source URL, quote) and usage scenarios. It explains what happens when optional parameters are omitted. However, it lacks explicit details on the exact response structure (e.g., field names like 'verdict', 'source_url'), which would be helpful for an agent to parse the result. Still, it provides enough context for effective use.

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% (all parameters have descriptions), so baseline is 3. The description adds value beyond the schema by clarifying behavior when optional parameters are omitted: 'Without it, every stored field is checked' (for field) and 'Without it, the dataset's stored values are searched for the claimed value' (for record_id). It also explains the match types and verdicts, providing richer semantics.

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: 'Check a claimed fact against a published record.' It explains what it reports (match types, source quote, URL) and lists possible verdicts. This verb+resource combination is distinct from sibling tools like get_record (fetch full record) or search_records (search for records), making it easy for an agent to differentiate.

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 instructs: 'Use this whenever you want to confirm a number, date, threshold or status before stating it.' This provides strong guidance on when to use the tool. It does not explicitly state when not to use it (e.g., if you need the full record, use get_record instead), but the sibling context and the clear purpose make the decision boundary reasonably clear.

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