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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds rich behavioral detail: the two routing paths, the exact verdict list, the pipeworx:// citation, and the crucial warning that could_not_verify means the check did not happen (not evidence). This goes well beyond annotations and clearly explains the two special verdict meanings.

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?

Though lengthy, every sentence earns its place: trigger phrases, usage guidance, path routing, output summary, and caller-critical warnings. The structure is logical and front-loaded, with the most actionable info (when to use) at the start. No redundancy or fluff.

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?

There is no output schema, so the description must fully explain return values. It lists the verdict types, the actual value with citation, reasoning, and explicitly distinguishes could_not_verify from unsupported. It also explains the two processing paths and tolerance behavior. This is complete for a complex tool with no output schema.

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%, with both parameters well-described in the schema. The description adds no additional information about parameter syntax or defaults; it only mentions tolerance indirectly ('exact percent-delta math'). Thus the schema carries the load, and the description adds minimal value, warranting the baseline 3.

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 strong trigger phrases ('Is it true that…', 'fact check') and immediately states the core function: natural-language claim verification against authoritative sources. It clearly distinguishes itself from sibling tools by focusing on factual claim verification, not entity resolution or comparison.

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?

It explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct.' It further differentiates sub-usage: company-financial claims go through SEC EDGAR fast path, all other claims fall through to the grounded pipeline. This provides clear context and routing guidance, though it does not name an alternative tool.

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