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

With no annotations, the description carries the burden of disclosing behavior. It clearly states what the tool returns (0-100 risk score, missing safeguards, revenue-at-risk estimate, integration kit) and implies a non-destructive audit via the word 'audit' and 'returns'. However, it does not explicitly state that it does not modify data, nor does it mention any auth or rate-limit constraints. The output description is strong, but a small gap remains.

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 two sentences with no filler. The use condition is front-loaded, and the alternative tools are mentioned compactly in the second sentence. It is appropriately sized for the information it conveys.

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 8 parameters and no output schema, the description covers the purpose, usage, and high-level output but fails to explain the boolean parameters or the contents of the 'integration kit'. It also does not describe the response format. The description is adequate for routing but leaves gaps for an agent that needs to fill all parameters correctly.

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 0%, so the description must compensate. It mentions 'monthly lead volume' and 'customer value' which map to monthly_leads and average_customer_value, but it does not name the parameters or explain the boolean 'safeguards' fields (stack, idempotency, retry_policy, failure_alerts, dead_letter_queue, destination_verification). The agent is left to guess which booleans correspond to 'current safeguards', making parameter semantics vague.

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 states a specific action (audit lead workflow) and its result (scored reliability diagnosis), and it differentiates from siblings by naming get_leadproof_evaluation_path and compare_leadproof_vs_in_house with their distinct use cases. This gives the agent enough to pick the right tool without 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?

It explicitly states when to use the tool (when buyer can provide monthly lead volume, customer value, and current safeguards) and gives explicit alternatives for other scenarios (general product tour, buy-or-build decision). This is a textbook example of usage guidance.

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