Lead screening

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

Annotations already indicate readOnlyHint=false and openWorldHint=true, and the description adds meaningful behavior details: the operation is web-grounded and consumes credits from the account wallet. This goes beyond the structured annotations and alerts the agent to a cost implication.

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?

One compact sentence communicates the transformation, the web-grounded nature, the evidence-based output, and the credit cost. Every element earns its place and the key input-to-output relationship is front-loaded.

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 two-parameter tool with no output schema, the description adequately explains both the expected output (qualification verdict with evidence) and an important side effect (credit cost). The agent has enough information to call the tool correctly and interpret its result.

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?

The input schema already has 100% coverage, with clear descriptions for both 'lead' and 'criteria'. The description only restates the conceptual role of the parameters ('A lead plus your ICP criteria') without adding format, syntax, or additional constraints, so it adds no semantic value beyond the schema.

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 defines the input (a lead plus ICP criteria), the operation (screening/qualification), and the output (a web-grounded qualification verdict with evidence for and against). This distinguishes it from sibling tools like parserail_classify or parserail_sentiment by specifying the qualification purpose and evidence-based result.

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?

The description gives clear context for when to use the tool: when the agent has a lead and ICP criteria and needs a qualification verdict. It does not explicitly name alternatives or exclusions, but the purpose is specific enough that an agent can infer appropriate usage.

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