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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive nature. The description adds critical behavioral context: the could_not_verify verdict meaning the check did not happen and must not be treated as evidence, the unsupported verdict meaning no source covers the claim, and details about the two distinct execution paths (structured vs. grounded). This goes well 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 longer than average but every sentence carries meaningful information: invocation examples, use cases, routing logic, verdict meanings, and error-handling caveats. It is front-loaded with examples and ends with the efficiency benefit. Slightly dense but well-structured and free of 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?

For a complex verification tool with no output schema, the description fully covers return values (six verdicts), the structured vs. grounded pipeline, citation format, and the critical difference between could_not_verify and unsupported. It also explains why the tool exists (replaces multiple sequential calls). Complete enough for an agent to use it correctly.

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?

Input schema already covers both parameters with high-quality descriptions (100% coverage). The description adds extra semantics by explaining the claim accepts natural-language phrases, the tolerance_pct overrides the wording-implied tolerance, and provides concrete examples. This enhances rather than repeats the schema.

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 states a specific verb+resource: natural-language claim verification against authoritative sources. It gives concrete invocation phrases and example claims. It also distinguishes itself from siblings by noting it replaces 4–6 sequential calls and by describing the fallback pipeline for non-financial 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?

It explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and clarifies that company-financial claims go through SEC EDGAR/XBRL while any other factual claim falls through to a grounded pipeline. However, it does not mention when NOT to use this tool or list alternative tools for non-factual queries, so it lacks explicit exclusions.

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