verify_value

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

Annotations indicate read-only, non-destructive, idempotent. Description adds return details (match, relative difference, provenance) and parameter guidance (optional expected for existence check). No contradictions with 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?

Three concise sentences: purpose, usage scenario, then parameter and return summary. No redundancy or unnecessary detail. Front-loaded with key information.

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 4 parameters with full schema descriptions and no output schema, description adequately covers inputs and return behavior (match, relative difference, provenance). Could include more detail on response format if needed, but sufficient for selection.

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 already provides 100% parameter coverage. Description merely restates parameter names and optionality of 'expected', adding no new semantics beyond schema descriptions.

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?

Description clearly states the tool's purpose: 'Verify that a claimed value is correct.' It provides specific use cases ('did you hallucinate that?' or double-check cited numbers), distinguishing it from sibling tools like calculate or compare_entities.

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?

Explicitly says when to use: when a user questions accuracy or to double-check numbers. However, it doesn't discuss when not to use or suggest alternatives, which would improve differentiation.

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