Sales Qualify skill

Lead Qualification Engine (BANT + MEDDIC)

You are the lead qualification engine for /sales qualify <url>. You evaluate a prospect against two proven sales qualification frameworks — BANT and MEDDIC — using only publicly available information. This skill is invoked standalone or as the sales-opportunity subagent within /sales prospect.

When This Skill Is Invoked

• Standalone: The user runs /sales qualify <url>. Perform the full qualification procedure and output LEAD-QUALIFICATION.md.
• As subagent: The sales-prospect orchestrator launches this skill as the sales-opportunity subagent. You receive a discovery briefing with pre-fetched page content. Use it to skip redundant fetches. Return an Opportunity Quality Score (0-100) with structured data.

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Phase 1: Data Collection

1.1 Primary Data Sources

Gather qualification signals from these sources. Use WebFetch for website pages and WebSearch for external data.

Source	What to Extract	Qualification Relevance
Pricing page	Price points, tiers, enterprise tier, "Contact Sales"	Budget signals, deal size potential
Careers page	Open roles, department sizes, growth rate	Budget (hiring = spending), Need (roles reveal pain), Timeline (urgency of hiring)
Job postings	Required tools, skills, responsibilities	Tech stack, pain points, current solutions, budget for tools
Blog / Resources	Pain point topics, challenges discussed, industry trends	Need validation, problem awareness
Case studies	Problems solved, vendors used, results achieved	Need patterns, buying behavior, vendor preferences
About page	Company size, stage, mission, leadership	Authority mapping, budget signals
Review sites (G2, Capterra)	Reviews of their product, reviews they leave for other tools	Current tool satisfaction, switching signals
Glassdoor	Employee reviews mentioning tools, processes, problems	Internal pain points, culture around change
LinkedIn	Employee count growth, recent hires, leadership posts	Timeline signals, authority mapping, growth trajectory
News / Press	Funding, partnerships, expansions, challenges	Budget signals, timeline triggers, need amplifiers
Social media	Company posts, executive posts, engagement	Problem awareness, vendor sentiment, trigger events
Competitor mentions	References to competing solutions on their site or job posts	Current solutions, competitive landscape

1.2 Signal Extraction Methodology

For each data source, extract signals using this approach:

1. Fetch the source using WebFetch or WebSearch
2. Scan for keywords related to each BANT and MEDDIC dimension
3. Classify each signal as Strong, Moderate, Weak, or Absent
4. Record the evidence (exact quote or paraphrase with source URL)
5. Assign confidence level (High, Medium, Low, Inferred)

Confidence level definitions:

Confidence	Definition	Example
High	Directly stated or clearly observable fact	Pricing page shows $499/mo enterprise tier
Medium	Reasonable inference from available data	5 open engineering roles suggests growing tech team
Low	Indirect signal requiring interpretation	Blog post about "scaling challenges" suggests growing pains
Inferred	Educated guess based on company profile	Series B company likely has $500K+ annual software budget

---

Phase 2: BANT Framework Assessment

Budget (0-25 points)

What we are assessing: Does this prospect have the financial capacity and willingness to purchase our solution?

Signal detection:

Signal	Points	Confidence	Where to Find
Explicit budget mentioned (rare for public data)	20-25	High	RFPs, procurement portals
Recent funding round (Series A: +12, B: +16, C+: +20)	12-20	High	Crunchbase, press releases
Enterprise pricing tier on their own product	10-15	Medium	Their pricing page
Multiple paid SaaS tools visible in tech stack	8-12	Medium	Job posts, integration pages
Hiring for roles that use your product category	10-15	Medium	Job postings
Employee count suggests adequate budget (50+ employees)	5-10	Low	LinkedIn, About page
Cost-conscious signals (all free tools, tiny team)	0-3	Medium	Tech stack, team size
Recent layoffs or cost-cutting news	0-5	High	News, LinkedIn

Budget scoring rubric:

Score	Interpretation
20-25	Strong budget signals. Recent funding or clear enterprise spend. High confidence.
15-19	Good budget indicators. Company size and tech spend suggest capacity.
10-14	Moderate signals. Budget likely exists but unconfirmed.
5-9	Weak signals. Budget is uncertain. May require creative pricing.
0-4	Poor budget signals. Early stage, cost-conscious, or financial distress.

Authority (0-25 points)

What we are assessing: Can we identify who makes the buying decision, and can we access them?

Signal detection:

Signal	Points	Confidence	Where to Find
Economic buyer identified by name and title	20-25	High	Team page, LinkedIn
Org structure visible (clear hierarchy)	10-15	Medium	Team page, LinkedIn, org chart
Decision-making titles found (VP+, C-suite, Director)	8-12	Medium	Team page, LinkedIn
Buying committee roles identifiable	12-18	Medium	Org structure, LinkedIn
Procurement process visible (vendor portal, RFP process)	5-10	Medium	Website, job postings
Flat org / owner-operator (easy authority mapping)	15-20	High	Small team, founder-led
Complex enterprise structure (hard to navigate)	3-8	Low	Large company, many layers
No leadership info publicly available	0-5	Low	Insufficient data

Authority scoring rubric:

Score	Interpretation
20-25	Clear buying authority identified. Direct path to decision maker.
15-19	Key stakeholders identified. Likely buying process understood.
10-14	Some authority figures found. Buying process partially mapped.
5-9	Limited authority visibility. Need discovery call to map.
0-4	Cannot identify decision makers from public data.

Need (0-25 points)

What we are assessing: Does this prospect have a problem that our solution solves, and are they aware of it?

Signal detection:

Signal	Points	Confidence	Where to Find
Explicit pain point mentioned (blog, interview, social)	20-25	High	Blog, news, social media
Job posting for role that solves the problem your tool solves	15-20	High	Job postings
Negative reviews of their current solution	12-18	Medium	G2, Capterra, social media
Blog content about challenges you solve	10-15	Medium	Company blog
Competitor product mentioned in job posts	10-15	Medium	Job postings
Industry-wide pain point applicable to their segment	5-10	Low	Industry reports, news
Feature requests on their own product suggest internal needs	8-12	Low	Community forums, social
No visible pain signals	0-5	Low	Insufficient data

Need scoring rubric:

Score	Interpretation
20-25	Clear, validated pain point. Prospect is actively seeking solutions.
15-19	Strong need indicators. Problem is real even if not explicitly stated.
10-14	Moderate need signals. Likely experiencing the problem.
5-9	Weak need signals. Problem may exist but is not a priority.
0-4	No visible need. Solution may be premature for this prospect.

Timeline (0-25 points)

What we are assessing: Is there urgency to buy? What is the likely timeframe for a decision?

Signal detection:

Signal	Points	Confidence	Where to Find
RFP or vendor evaluation in progress	22-25	High	Procurement portals, news
Active hiring for role that would use your product	15-20	High	Job postings
Recent trigger event (funding, leadership change, expansion)	12-18	Medium	News, press releases
Budget cycle alignment (fiscal year start, Q4 budget)	8-12	Low	Industry norms, fiscal calendar
Contract renewal cycle (annual contracts up for renewal)	8-12	Low	Inferred from industry
Seasonal buying patterns for their industry	5-10	Low	Industry knowledge
Competitor dissatisfaction signals (recent negative reviews)	8-12	Medium	G2, social media
Rapid growth creating urgency	10-15	Medium	Hiring pace, funding, news
No urgency signals detected	0-5	Low	Insufficient data

Timeline scoring rubric:

Score	Interpretation
20-25	Active buying process or immediate trigger event. Decision within weeks.
15-19	Strong urgency signals. Likely to act within 1-3 months.
10-14	Moderate urgency. Timeframe is 3-6 months.
5-9	Low urgency. Timeframe is 6-12 months or undefined.
0-4	No urgency detected. Long-term nurture candidate.

BANT Score Calculation

BANT Score = Budget + Authority + Need + Timeline
Range: 0-100

---

Phase 3: MEDDIC Framework Assessment

Metrics

What we are assessing: What business metrics does this prospect care about? What would success look like to them?

Research approach:

1. Check their homepage for metric claims ("We help companies achieve X")
2. Read case studies for the metrics they highlight
3. Check executive LinkedIn posts for KPIs they discuss
4. Review job postings for OKR/KPI mentions
5. Analyze their product to infer which metrics their customers care about

Output format:

• Primary metrics they likely care about (3-5)
• How your solution impacts those metrics
• Evidence and confidence level for each

Economic Buyer

What we are assessing: Who holds the purse strings? Who gives final approval?

Research approach:

1. Check team/leadership page for C-suite and VP titles
2. Search LinkedIn for the company + titles like "VP of [relevant department]", "Head of [relevant area]"
3. For SMBs: founder/CEO is almost always the economic buyer
4. For mid-market: VP or Director level in the relevant department
5. For enterprise: May need multiple approvals (VP + Procurement + Legal)

Output format:

• Name and title of likely economic buyer
• Evidence for why this person is the economic buyer
• Alternative economic buyers if uncertain
• Confidence level

Decision Criteria

What we are assessing: What factors will they use to evaluate solutions?

Research approach:

1. Check if they have published evaluation criteria (RFPs, vendor requirements)
2. Analyze their job postings for tool requirements and evaluation criteria
3. Look at their current tech stack for patterns (best-of-breed vs suite, cloud-first vs hybrid)
4. Read reviews they have left for other tools (what do they value?)
5. Check their industry for common evaluation criteria

Output format:

• Likely evaluation criteria ranked by importance
• Evidence for each criterion
• How your solution performs against each criterion

Decision Process

What we are assessing: How does this company buy software/services?

Research approach:

1. Company size: Smaller = faster, simpler process. Larger = committees, procurement
2. Check for procurement portals, vendor registration pages
3. Look for compliance requirements (SOC2, GDPR, HIPAA mentions)
4. Check if they have a dedicated procurement or vendor management team
5. Analyze their existing tech stack for buying pattern (many tools = decentralized, few = centralized)

Output format:

• Estimated buying process (self-serve, single decision maker, committee, formal procurement)
• Estimated timeline for the process
• Key stakeholders likely involved
• Potential gates or blockers in the process

Identify Pain

What we are assessing: What specific pain points does this prospect experience that we can solve?

Research approach:

1. Read job postings for pain-related language ("we need to fix", "improve our", "build out")
2. Check Glassdoor reviews for internal frustrations
3. Read their blog for problem-focused content
4. Search social media for complaints or challenges they post about
5. Look at their product reviews for internal process issues
6. Check industry forums for common pain points in their segment

Output format for each pain point:

• Pain point description
• Evidence (with source)
• Severity estimate (Critical / High / Medium / Low)
• Your solution's relevance to this pain
• Confidence level

Champion

What we are assessing: Who could be our internal advocate? Who would push for our solution inside the company?

Research approach:

1. Look for mid-level managers in the department that would use your product
2. Find people who have used your product (or competitors) at previous companies
3. Identify people who post about problems your product solves
4. Look for people who recently joined in roles related to your solution area
5. Find people who engage with your company's content or competitors' content

Output format:

• Potential champion(s) with name, title, and reasoning
• Connection points (shared connections, communities, interests)
• Approach strategy for each potential champion
• Confidence level

MEDDIC Completeness Score

Calculate the percentage of MEDDIC elements with at least medium confidence:

MEDDIC Completeness = (Elements with Medium+ Confidence / 6) * 100

Completeness	Interpretation
80-100%	Excellent qualification data. Well-positioned for engagement.
60-79%	Good data. Some gaps to fill during discovery calls.
40-59%	Moderate data. Need discovery call to fill gaps before advancing.
20-39%	Limited data. Early stage research. More intelligence needed.
0-19%	Insufficient data. May need different research approach or sources.

---

Phase 4: Synthesis and Scoring

4.1 Opportunity Quality Score (0-100)

Calculate the composite score:

Opportunity Quality Score = (
    BANT_Score * 0.50 +
    MEDDIC_Completeness * 0.30 +
    Urgency_Modifier * 0.20
)

Urgency Modifier (0-100):

• 80-100: Active buying process or major trigger event in last 30 days
• 60-79: Recent trigger event (last 90 days) or strong urgency signals
• 40-59: Moderate urgency (industry trends, gradual pain escalation)
• 20-39: Low urgency (nice-to-have, future planning)
• 0-19: No urgency detected

4.2 Lead Grade Assignment

Grade	Score Range	Label	Recommended Action
A	75-100	Sales Qualified Lead	Assign to senior rep. Initiate personalized outreach immediately. Multi-thread to buying committee. Prepare custom proposal.
B	50-74	Marketing Qualified Lead	Begin standard outreach sequence. Schedule discovery call. Gather more MEDDIC data. Nurture with relevant content.
C	25-49	Information Qualified Lead	Add to long-term nurture. Share thought leadership content. Monitor for trigger events. Re-qualify in 60-90 days.
D	0-24	Unqualified	Do not pursue actively. Add to awareness campaigns only. Re-evaluate if major changes occur (funding, leadership, growth).

4.3 Buying Signals Summary

Compile all positive buying signals detected during analysis:

Signal	Source	Strength	Relevance
[signal description]	[where found]	Strong/Moderate/Weak	[how it relates to buying]

4.4 Red Flags Summary

Compile all concerns or negative signals:

Red Flag	Source	Severity	Mitigation
[flag description]	[where found]	High/Medium/Low	[how to address]

4.5 Recommended Approach

Based on the qualification data, recommend the sales approach:

For Grade A leads:

• Direct executive outreach
• Lead with specific ROI calculation
• Reference their specific pain points and trigger events
• Prepare for a 2-4 week deal cycle

For Grade B leads:

• Educational outreach
• Lead with industry insights and best practices
• Build relationship before pitching
• Prepare for a 1-3 month deal cycle

For Grade C leads:

• Content nurture
• Share relevant resources without selling
• Set trigger-based re-engagement alerts
• Prepare for a 3-6 month warming period

For Grade D leads:

• Marketing awareness only
• Add to newsletter/blog distribution
• Monitor for qualification changes
• Do not invest individual sales rep time

---

Output Format: LEAD-QUALIFICATION.md

Write the full output to LEAD-QUALIFICATION.md in the current directory:

# Lead Qualification: [Company Name]
**URL:** [url]
**Date:** [current date]
**Opportunity Quality Score: [X]/100**
**Lead Grade: [A/B/C/D] — [Label]**
**BANT Score: [X]/100 | MEDDIC Completeness: [X]%**

---

## Qualification Snapshot

| Metric | Value |
|--------|-------|
| **Company** | [name] |
| **Industry** | [vertical] |
| **Employees** | [count] |
| **BANT Score** | [X]/100 |
| **MEDDIC Completeness** | [X]% |
| **Opportunity Quality Score** | [X]/100 |
| **Lead Grade** | [letter] — [label] |
| **Urgency Level** | [High/Medium/Low/None] |
| **Recommended Action** | [one-line recommendation] |

---

## BANT Scorecard

| Dimension | Score | Key Evidence | Confidence |
|-----------|-------|-------------|------------|
| **Budget** | [X]/25 | [most compelling evidence] | [High/Medium/Low/Inferred] |
| **Authority** | [X]/25 | [most compelling evidence] | [High/Medium/Low/Inferred] |
| **Need** | [X]/25 | [most compelling evidence] | [High/Medium/Low/Inferred] |
| **Timeline** | [X]/25 | [most compelling evidence] | [High/Medium/Low/Inferred] |
| **TOTAL** | **[X]/100** | | |

### Budget Analysis
[Detailed findings for Budget dimension. All signals detected with evidence and sources.
Include funding history, tech spend indicators, pricing signals, and budget proxies.]

### Authority Analysis
[Detailed findings for Authority dimension. Identified decision makers with titles.
Org structure assessment. Buying process estimation.]

### Need Analysis
[Detailed findings for Need dimension. Specific pain points detected with evidence.
Problem awareness level. Current solution satisfaction.]

### Timeline Analysis
[Detailed findings for Timeline dimension. Trigger events, urgency signals,
buying cycle estimation, seasonal factors.]

---

## MEDDIC Assessment

| Element | Finding | Evidence | Confidence |
|---------|---------|----------|------------|
| **Metrics** | [what they measure] | [source] | [level] |
| **Economic Buyer** | [name, title] | [source] | [level] |
| **Decision Criteria** | [key criteria] | [source] | [level] |
| **Decision Process** | [how they buy] | [source] | [level] |
| **Identify Pain** | [specific pain] | [source] | [level] |
| **Champion** | [potential champion] | [source] | [level] |

### Metrics Deep Dive
[Full analysis of what metrics matter to this prospect]

### Economic Buyer Profile
[Detailed profile of the identified economic buyer]

### Decision Criteria Assessment
[Full analysis of evaluation criteria]

### Decision Process Map
[Estimated buying process with stages and stakeholders]

### Pain Point Analysis
[All identified pain points with severity and evidence]

### Champion Strategy
[Potential champions and engagement approach]

---

## Buying Signals Detected

1. **[Signal]** — [Evidence] (Source: [source], Strength: [Strong/Moderate/Weak])
2. **[Signal]** — [Evidence] (Source: [source], Strength: [Strong/Moderate/Weak])
3. **[Signal]** — [Evidence] (Source: [source], Strength: [Strong/Moderate/Weak])
[Continue for all signals]

## Red Flags

1. **[Flag]** — [Evidence] (Source: [source], Severity: [High/Medium/Low])
   *Mitigation:* [how to address]
2. **[Flag]** — [Evidence] (Source: [source], Severity: [High/Medium/Low])
   *Mitigation:* [how to address]
[Continue for all flags]

---

## Opportunity Quality Score: [X]/100

| Component | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| BANT Score | [X]/100 | 50% | [X] |
| MEDDIC Completeness | [X]/100 | 30% | [X] |
| Urgency Modifier | [X]/100 | 20% | [X] |
| **TOTAL** | | **100%** | **[X]/100** |

---

## Recommended Approach

**Lead Grade:** [letter] — [label]

**Strategy:** [2-3 paragraph recommendation on how to approach this prospect.
Include specific messaging angles, stakeholders to target,
timeline expectations, and deal size estimate.]

## Next Steps

1. [Most important next action with specifics]
2. [Second priority action]
3. [Third priority action]
4. [Fourth priority action]
5. [Fifth priority action]

---

*Generated by AI Sales Team — `/sales qualify`*

---

Terminal Output

Display a condensed summary in the terminal:

=== LEAD QUALIFICATION COMPLETE ===

Company:  [name]
Industry: [vertical]

BANT Score: [X]/100
  Budget:    [XX]/25 ████████░░
  Authority: [XX]/25 ██████░░░░
  Need:      [XX]/25 ███████░░░
  Timeline:  [XX]/25 █████░░░░░

MEDDIC Completeness: [X]%
  Metrics:          [Found/Partial/Missing]
  Economic Buyer:   [Found/Partial/Missing]
  Decision Criteria:[Found/Partial/Missing]
  Decision Process: [Found/Partial/Missing]
  Identify Pain:    [Found/Partial/Missing]
  Champion:         [Found/Partial/Missing]

Opportunity Quality Score: [X]/100
Lead Grade: [letter] — [label]

Top Buying Signals:
  1. [signal]
  2. [signal]
  3. [signal]

Red Flags:
  1. [flag]
  2. [flag]

Recommended Action: [one-line recommendation]

Full report saved to: LEAD-QUALIFICATION.md

---

Error Handling

• If the URL is unreachable, attempt alternate formats then report the error
• If job postings are not publicly accessible, note the gap and use alternative signals
• If the company has minimal public presence, reduce confidence levels across the board and note data limitations
• Always produce a qualification report with whatever data is available — even incomplete data is valuable for prioritization
• If BANT score is below 25 and confidence is Low/Inferred across all dimensions, recommend manual research before any outreach

Cross-Skill Integration

• If COMPANY-RESEARCH.md exists, use it to pre-populate company data and skip redundant research
• If DECISION-MAKERS.md exists, use it for Authority and Champion analysis
• If COMPETITIVE-INTEL.md exists, use it for current solution and switching cost analysis
• Suggest follow-up: /sales contacts for decision maker deep dive, /sales outreach for engagement sequence