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

Beyond the annotations (readOnlyHint true, openWorldHint false), the description discloses deterministic behavior, fixed text-pattern rules, outputs (structured score, flags, fixes, template), and that it runs without an AI model. This adds significant behavioral context not captured by annotations alone.

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 concise and front-loaded: the first sentence states the core purpose and the six rules, followed by output details and usage guidance. No redundant sentences; every clause adds useful 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?

For a simple tool with one required parameter and no output schema, the description completely covers what it does, how it behaves, what it returns, and when to use it vs. alternatives. Nothing essential is missing.

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% for the single parameter 'text', which is described as 'What the salesperson said when offering the appointment'. The tool description adds value by explaining how the text is evaluated (six fixed rules) and that detected day/time are reused in the template, giving the agent better context on what content to provide, though it doesn't introduce new parameter constraints.

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 as a deterministic check of an appointment ask using six specific text-pattern rules, and it distinguishes itself from the sibling review_appointment_ask. It states the verb (check), the resource (appointment ask), and the exact evaluation criteria, leaving no ambiguity.

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 instructs when to use this tool versus the alternative: 'Use this for repeatable rule-based scoring; use review_appointment_ask for contextual AI feedback and a tailored rewrite.' Also notes that it runs without an AI model, giving clear context for selection.

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