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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so safety is covered. The description adds high-value behavioral context beyond that: it enumerates the six possible verdicts, explains that 'could_not_verify' means a failed check (not evidence against the claim) and carries a structured error, and clarifies that 'unsupported' means no source was found. This prevents dangerous misinterpretation of results and discloses the two-path routing behavior.

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 the minimal example but every section earns its place: trigger phrases, purpose, routing logic, return values, and a critical caller warning. It is front-loaded with the most important info (what it does) and structured with a clear 'IMPORTANT' callout. Minor redundancy exists between 'natural-language claim verification' and the subsequent 'Use whenever' sentence, but overall it is tightly written for the complexity.

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 no output schema, the description does an excellent job covering return values (verdict enum, actual value, citation, reasoning), error semantics (could_not_verify vs unsupported), routing logic (company-financial vs other), and efficiency (replaces 4–6 calls). It provides enough operational context for an agent to use the tool correctly and interpret results accurately, even without seeing the 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% and both parameters (claim, tolerance_pct) already have rich descriptions with examples and constraints. The description adds only marginal value about parameters itself (e.g., 'exact percent-delta math'), while the schema fully documents the meaning and default behavior. Baseline of 3 is appropriate since the description doesn't need to compensate for schema gaps.

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 clear natural-language triggers ('Is it true that…', 'fact check', 'verify the claim that…') and immediately states a specific verb+resource: natural-language claim verification against authoritative sources. It also distinguishes itself from sibling tools by explicitly framing the task as claim verification (not general Q&A) and noting it replaces 4–6 sequential calls, showing it is the dedicated fact-checking tool.

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 gives an explicit 'Use whenever the agent needs to check whether something a user said is factually correct' and explains how different claim types route (SEC EDGAR path vs. grounded pipeline). It does not explicitly name alternative tools or state when NOT to use it, but the built-in routing and claim-specific context make the intended usage clear relative to siblings like ask_pipeworx.

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