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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses crucial behaviors: the meaning of could_not_verify (verification did not happen, not evidence), unsupported (coverage gap), the routing logic, verbatim evidence, pipeworx:// citations, and the consolidation of multiple sequential calls. This is rich, non-obvious context with no contradiction to 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 longer than average, but every sentence earns its place: trigger phrases, usage directive, dual-path explanation, return structure, caller warnings, and performance rationale. It is front-loaded with easy-to-recognize phrasings and progresses logically to edge cases. No redundancy or filler.

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?

For a tool without an output schema, the description is exceptionally thorough: it enumerates the possible verdicts, describes the evidence and citation format, explains the two failure semantics, and covers routing logic. Agents receive enough detail to invoke correctly and interpret results safely, with no ambiguity left.

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 the description adds significant meaning: it explains that tolerance_pct overrides the tolerance implied by the claim wording, defaults at 5%, and recommends 1–2% for hallucination detection. It also gives a concrete example for the claim parameter, clarifying expected natural-language format.

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 trigger phrases and a specific verb ('validate', 'verify', 'fact check', 'confirm or refute') tied to the claim resource. It clearly differentiates from sibling tools by describing the dual-path pipeline (SEC EDGAR for financial claims, grounded pipeline for all others) and positions itself as a replacement for multi-step orchestration.

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 states when to use: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also distinguishes the financial structure path from the general grounded path, giving agents context about which claims benefit from the fast path. No explicit exclusions, but the guidance is concrete and decision-ready.

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