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

Beyond the readOnly/idempotent annotations, the description discloses verdict values, the critical semantics of could_not_verify (not evidence for/against), the meaning of unsupported, and the internal routing. It also warns callers about verification_error, adding substantial context that the annotations alone do not convey.

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 organized: trigger phrases, use context, routing logic, return types, and an IMPORTANT caller warning. It is longer than average but every sentence contributes useful information; only slight verbosity prevents a 5.

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 specifies return values (verdict, actual value, citation, reasoning) and distinguishes important edge cases (could_not_verify vs unsupported). This makes the tool's behavior predictable and complete for an agent.

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 description coverage is 100%, and both parameters are already well-documented in the schema. The tool description adds no parameter-specific meaning beyond what the schema provides, so the 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 identifies the tool's function: natural-language claim verification against authoritative sources, with a specific verb ('verify'), a resource ('authoritative sources'), and concrete trigger phrases. It also distinguishes itself from siblings by noting it replaces 4–6 sequential calls and handles both structured company-financial claims and a grounded fallback for other 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 states 'Use whenever the agent needs to check whether something a user said is factually correct' and provides clear routing guidance: company-financial claims take the SEC EDGAR + XBRL path, any other factual claim falls through to the grounded pipeline. However, it does not explicitly mention when NOT to use this tool or compare it to alternatives like ask_pipeworx_grounded, so it loses a point.

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