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crm_lead_qualification

Qualifies a lead against your ideal customer profile by analyzing firmographic data, intent signals, and past interactions, then assigns a grade (A-D), returns a fit score, reasoning, and a suggested next-best-action.

Instructions

Qualify a lead against your ICP and grade it (A/B/C/D). Pulls firmographic data, intent signals, and prior interactions; returns a fit score, the reasoning, and a suggested next-best-action. Args: message: Free-text objective for the action. lead_id: CRM lead/contact ID. lead_email: Lead email (alternative to lead_id). company_domain: Company domain to enrich from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
lead_idNo
lead_emailNo
company_domainNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It describes what the tool does but does not disclose behavioral traits like side effects, permissions needed, error conditions, idempotency, or whether it modifies CRM data. The description only states actions, not behavioral consequences.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one short paragraph plus a structured Args block. The main purpose is front-loaded in the first sentence. It is efficient with no redundant text, but the Args block could be integrated more smoothly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple inputs, multiple outputs), the description covers the main purpose and output types (fit score, reasoning, next-best-action). An output schema exists, so return details are covered elsewhere. However, it omits context about prerequisite setups (e.g., ICP definition) and error handling, making it moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 provides brief descriptions for all four parameters (message, lead_id, lead_email, company_domain) explaining their roles, including that lead_email is an alternative to lead_id. This adds meaning beyond the raw schema, though some parameter constraints or formats are missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool qualifies a lead against an ICP and grades it (A/B/C/D), and lists what data it pulls and returns. It is specific about the verb and resource, but does not differentiate from sibling CRM tools like crm_enrich_lead or crm_verify_lead, so sibling differentiation is missing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus alternatives. No 'use this when' or 'instead of X' statements. The description implies it is for lead qualification but does not set clear usage boundaries.

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

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