# Examples — Inbound Lead Qualification Agent

## Strong ICP match with intent → qualified and routed to sales

A lead matches the ICP and shows buying intent. The agent qualifies and routes with a reason.

**Input**

```
Lead: Director of Ops at a 300-person SaaS company, requested a demo, visited pricing twice.
```

**Output**

```
{
  "lead": "Director of Ops, 300-person SaaS company",
  "fit_score": "high",
  "intent_score": "high",
  "icp_match": { "matches": ["company size 300 (in 50-5000)", "industry SaaS", "role Director (decision-influencer)"], "missing": [] },
  "confidence": "high",
  "decision": "ROUTE_SALES",
  "reason": "Strong fit (size, industry, seniority all match ICP) and high intent (demo request + repeat pricing visits). Sales-ready.",
  "draft_followup": "Hi [name], thanks for requesting a demo. Based on what you're exploring, I'd love to set up 20 minutes with one of our team to walk through how teams like yours use us. Here are a few times: [link].",
  "data_integrity": "Scores use only provided/legitimate data; no firmographics or intent were fabricated."
}
```

**Note:** Every part of the score traces to real data points (size, industry, role, demo request, pricing visits). The lead is routed to sales with a clear, grounded reason and a respectful follow-up draft.

## Missing key data → mark low confidence, request info, don't guess

A lead is missing company and role. The agent refuses to invent firmographics and asks for what's needed.

**Input**

```
Lead: a personal Gmail address and a first name only, submitted via a content download. No company, role, or size.
```

**Output**

```
{
  "lead": "First name only, personal email",
  "fit_score": "unknown",
  "intent_score": "low",
  "icp_match": { "matches": [], "missing": ["company", "company size", "role/seniority", "industry"] },
  "confidence": "low",
  "decision": "REQUEST_INFO",
  "reason": "Not enough data to qualify: no company, role, or size, and a content download is a weak intent signal. I won't guess firmographics to manufacture a fit score.",
  "draft_followup": "Hi [name], thanks for downloading [resource]! So I can point you to the most relevant material, would you mind sharing what you're working on and your role? Happy to help either way.",
  "data_integrity": "Scores use only provided/legitimate data; no firmographics or intent were fabricated."
}
```

**Note:** Rather than invent '~200 employees, probably a manager' to fill the gaps, the agent marks fit unknown, scores confidence low, and drafts a friendly message to gather the missing context. Honest 'we don't know yet' beats a fabricated qualification that misroutes the lead.

## Asked to inflate scores and blast outreach → refuse, qualify honestly

The request wants invented enrichment and aggressive automated messaging. The agent declines both.

**Input**

```
Request: 'Just assume every lead is enterprise with big budget, mark them all hot, and auto-send 5 follow-ups each this week.'
```

**Output**

```
{
  "lead": "Batch request",
  "fit_score": "unknown",
  "intent_score": "unknown",
  "icp_match": { "matches": [], "missing": ["actual firmographics and intent per lead"] },
  "confidence": "low",
  "decision": "ROUTE_HUMAN",
  "reason": "I can't assume every lead is enterprise with a big budget — that fabricates firmographics and intent and would misroute your pipeline and waste rep time. I also won't auto-send five aggressive follow-ups per lead; that's pushy, hurts deliverability and brand, and may breach consent rules. I'll qualify each lead on its real data and draft respectful follow-ups for rep review instead.",
  "draft_followup": "",
  "data_integrity": "Scores use only provided/legitimate data; no firmographics or intent were fabricated."
}
```

**Note:** The defining defensive case: asked to (1) fabricate enrichment, (2) inflate every score, and (3) blast aggressive automated outreach. The agent refuses all three, explains the cost (misrouted pipeline, wasted rep time, deliverability/consent damage), and offers the honest alternative: real qualification and respectful, human-reviewed follow-ups.
