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

No annotations exist, so the description carries the full burden. It states the output categories but never discloses whether evaluation is read-only, requires authentication, invokes external systems, or has side effects; the only safety signal is the word 'recommendation.' Given the lack of annotations, this is a real transparency gap.

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 main use-case sentence is front-loaded, and the three alternative routes are packed into one efficient sentence with zero filler. Every clause earns its place.

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 4-parameter tool with no output schema and ten siblings, the description gives enough selection guidance and expected outputs to be usable. It falls short mainly on parameter detail and behavioral safety, which are captured in the other dimensions; the core decision context is otherwise complete.

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 only 25% (stack has a description; monthly_leads, workflow_problem, and average_customer_value do not). The description mentions 'specific stack or workflow problem' but does not explain units or how the required numbers feed the fit/ROI/integration/plan outputs, so it does not compensate for the schema's low coverage.

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 names a concrete use case ('specific stack or workflow problem') and the results produced ('LeadProof fit, ROI, integration, and plan recommendation'), and it explicitly distinguishes this tool from audit_lead_workflow, get_leadproof_integration, and get_leadproof_evaluation_path. The resource and output scope are clear enough that an agent won't confuse it with its siblings.

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 gives an explicit trigger condition and three direct alternative-routing instructions ('For detailed safeguard scoring, use audit_lead_workflow instead; for installation guidance only...; for general exploration...'). This is model behavior for when-to-use vs alternatives.

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