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

The description goes far beyond annotations by disclosing the two execution paths (SEC EDGAR fast path vs grounded pipeline), the exact verdict values returned, and critical clarifications: could_not_verify indicates no check happened and must not be used as evidence, while unsupported means no source was found. It also mentions the verification_error field. This is rich behavioral detail.

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 longer than necessary but every sentence adds value. It is front-loaded with example phrasings, then explains purpose, routing, return values, and important edge cases. The structure is logical, though it could be trimmed slightly without losing critical information.

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?

With no output schema, the description fully covers return values (verdict list, actual value with citation, reasoning) and error semantics. It also clarifies the unsupported verdict and the compound nature, making it complete for an agent to invoke correctly. Annotations cover read-only/idempotent safety, so nothing is missing.

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 provides 100% coverage for both parameters, with clear descriptions for claim and tolerance_pct. The tool description does not add significant extra meaning about how parameters are used, though it indirectly references tolerance through 'exact percent-delta math'. Baseline 3 is appropriate.

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 verifies natural-language factual claims against authoritative sources, with specific verbs like 'fact check' and 'verify the claim that'. It distinguishes itself from generic query tools by detailing its specialized claim-verification role and the compound nature replacing multiple sequential calls.

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?

Explicitly tells when to use: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also distinguishes between company-financial claims and other claims, giving clear routing guidance. However, it does not directly name sibling alternatives like ask_pipeworx_grounded, so it misses explicit exclusions.

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