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

Even though annotations already indicate read-only, idempotent, and non-destructive behavior, the description adds substantial context: dual pipeline behavior, exact percent-delta math, verdict semantics, and the critical distinction between 'could_not_verify' (check did not happen) and 'unsupported' (no source). It also warns callers not to treat a validation failure as evidence, which is valuable beyond the structured fields.

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 front-loaded with trigger phrases and purpose, then moves through routing, return values, and important caller warnings. It is moderately long but every sentence adds value: examples, verdict list, error semantics, and a note about replacing multiple calls. There is no filler or 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?

Since there is no output schema, the description must explain return values, and it does: verdicts, actual value with citation, reasoning, and verification_error details. It also covers failure modes, the unsupported case, and the efficiency benefit. For a complex two-path claim verification tool, this is complete.

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 fully (100% with examples and constraints), so the description does not need to compensate. It does add slight context about percent-delta math and tolerance behavior, but the schema carries the heavy lifting. This matches the baseline for high schema coverage.

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 concrete trigger phrases ('Is it true that…', 'fact check', 'verify the claim that…') and states 'natural-language claim verification against authoritative sources.' It clearly identifies the tool's verb (validate/verify) and resource (claims), and distinguishes it from sibling research/compare tools by focusing on fact-checking user statements.

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' and explains the routing for company-financial vs. other claims. It also notes it 'replaces 4–6 sequential calls,' giving practical guidance. However, it does not explicitly name alternative sibling tools to avoid or state when not to use it, so it falls just short of a 5.

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