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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, so the safety profile is covered. The description adds substantial behavioral context: two execution paths (SEC EDGAR vs. grounded pipeline), the exact verdict set, and a critical caveat that could_not_verify means the check failed and must not be interpreted as evidence. This goes far beyond the 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 dense but well-structured, front-loading purpose with trigger phrases, then routing logic, return values, and caveats. At about 180 words it's long but justified by the tool's complexity. Each section earns its place, though it could be slightly tightened.

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?

Even without an output schema, the description fully explains the returned verdicts, evidence links, and reasoning. It covers edge cases like could_not_verify vs. unsupported, which is crucial for correct interpretation. The description is complete and self-contained for the tool's complexity.

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%, so baseline is 3. The description adds meaningful parameter guidance: tolerance_pct overrides implied tolerance, recommends 1-2 for hallucination detection, and states the default cap of 5. It also gives example claims in the schema. This extra context improves the agent's ability to set and interpret parameters.

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 explicitly identifies the tool as natural-language claim verification against authoritative sources, with trigger phrases like 'fact check' and 'verify the claim that...'. It clearly distinguishes itself from general Q&A or research tools by focusing on binary verdicts for factual claims.

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 states 'Use whenever the agent needs to check whether something a user said is factually correct,' which is an explicit when-to-use. It also explains the automatic routing for financial vs. other claims and notes it replaces 4-6 sequential calls. However, it doesn't name specific alternative tools for non-claim tasks, so it lacks explicit when-not-to-use guidance.

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