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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior, but the description adds significant value by explaining the internal pipeline split, the exact meaning of verdicts like could_not_verify and unsupported, and the critical warning not to treat could_not_verify as evidence. This goes beyond the annotations and prevents misuse.

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 long but well-structured, starting with purpose, then usage guidance, then behavioral details and caveats. Every major point is useful, though the initial enumeration of example phrases is somewhat verbose and could be trimmed without losing meaning.

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 the absence of an output schema, the description fully specifies the return payload (verdict, actual value, citation, reasoning) and interprets the ambiguous verdicts. It also covers the two execution paths and error semantics, making it self-sufficient for a complex tool with no formal output definition.

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?

The input schema already provides complete descriptions for both parameters (claim and tolerance_pct), achieving 100% schema_description_coverage. The description adds no additional parameter-specific guidance, so the baseline of 3 is appropriate; it doesn't need to compensate for 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 explicitly states 'natural-language claim verification against authoritative sources' with clear invocation examples, distinguishing it from siblings like ask_pipeworx_grounded by focusing on verdict-based fact-checking. It also highlights that it 'Replaces 4–6 sequential calls', further cementing its unique role.

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 usage rule: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also details the two routing paths (SEC EDGAR for company-financial claims, grounded pipeline for all other claims), providing clear context for when to invoke versus alternatives. Mentioning that it replaces multiple sequential calls reinforces the decision to use it.

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