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

Annotations already declare readOnly=true, idempotent=true, destructive=false and openWorld=false, so the safety profile is covered. The description adds the computational method (segmenting by email domain and weighting close rates), which is useful, but says nothing about the shape or interpretation of the resulting 'quality score'.

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 first sentence is front-loaded and dense with the actual computation. The second sentence is a promotional link to an external calculator, which does not help the agent invoke the tool and is dead weight, but the core remains tight.

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?

With no output schema, the description should clarify what is returned (a score, segment breakdown, benchmark?) but only says 'score overall lead quality'. For a computational tool with four required inputs, that leaves the agent guessing about the result's form and scale.

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%, so all four parameters (signups, corporate email share, corporate and personal close rates) are documented in the schema. The description mirrors the corporate/personal split but adds no units, ranges, or format detail beyond what the schema already provides — baseline 3.

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?

States specific actions: split signups into corporate vs personal email intent segments, apply differentiated close rates, and score lead quality. This distinguishes it somewhat from siblings like lead_grading_calculator or lead_scoring_logic_architect, though it does not explicitly name how it differs from them.

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?

No when-to-use guidance, prerequisites, or named alternatives are given. The agent must infer from the name and description alone that this is the right pick over the many other lead-scoring tools in the sibling list.

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