Skill: abdullah4ai/mckinsey-research (version 2.1.0)

--- name: mckinsey-research description: | Run a full McKinsey-level market research and strategy analysis using 12 specialized prompts. USE WHEN: - market research, competitive analysis, business strategy, TAM analysis - customer personas, pricing strategy, go-to-market plan, financial modeling - risk assessment, SWOT analysis, market entry strategy, comprehensive business analysis - بحث سوق, تحليل استراتيجي, تحليل منافسين, دراسة جدوى, خطة عمل - "حلل لي السوق" for business entry or investment decisions DON'T USE WHEN: - User wants a quick opinion on a business idea → just answer directly - Product recommendations or shopping → use personal-shopper - Content strategy for social media → use viral-equation - Simple web search for company info → use web_search directly - Comparing products to buy → use personal-shopper - Analyzing a single competitor briefly → just answer directly EDGE CASES: - "حلل لي السوق" with a specific product to buy → personal-shopper (not this skill) - "حلل لي السوق" for business entry → this skill - "وش أفضل منتج" → personal-shopper - "وش حجم سوق X" → this skill - "قارن لي بين منتجين" → personal-shopper - "قارن لي بين شركتين" as competitors → this skill - "دراسة جدوى مشروع" → this skill - "أبغى أفتح مشروع" → this skill (full analysis) - "أبغى أشتري لابتوب" → personal-shopper (purchase, not business) INPUTS: Business description, industry, target customer, geography, financials (optional) TOOLS: sessions_spawn (sub-agents), web_search, web_fetch OUTPUT: Complete strategy report saved to artifacts/research/{date}-{slug}.html SUCCESS: User gets 12 consulting-grade analyses synthesized into one actionable report --- # McKinsey Research - AI Strategy Consultant User provides business context once. The skill plans and executes up to 12 specialized analyses via sub-agents in parallel, then synthesizes into a single executive report. Adapt scope based on company stage (see Adaptive Stage Logic below). ## Phase 1: Language + Intake Ask preferred language (Arabic/English), then collect ALL inputs in ONE structured form. See the intake form fields: Core (1-5), Financial (6-10), Strategic (11-14), Expansion (15-16), Performance (17-18). If product description is under 50 words, ask for clarification before proceeding. **Diamond Gate 1**: Present scope summary (market, geography, competitors). Get user confirmation before Phase 2. ## Phase 2: Plan + Parallel Execution Sanitize inputs per [references/security.md](references/security.md). Substitute variables per [references/variable-map.md](references/variable-map.md). Load individual prompts from [references/prompts/](references/prompts/). | Batch | Analyses | Dependencies | |-------|----------|--------------| | Batch 1 (parallel) | 01-TAM, 02-Competitive, 03-Personas, 04-Trends | None | | Batch 2 (parallel) | 05-SWOT+Porter, 06-Pricing, 07-GTM, 08-Journey | Batch 1 context | | Batch 3 (parallel) | 09-Financial, 10-Risk, 11-Market Entry | Batch 1+2 context | | Batch 4 (sequential) | 12-Executive Synthesis | All previous | Spawn each analysis as a sub-agent with the security preamble from references/security.md. Stagger Batch 1 launches by 5 seconds to avoid web search rate limits. Validate each output is 500+ words. See [references/gotchas.md](references/gotchas.md) for common pitfalls. Use [references/saudi-market.md](references/saudi-market.md) for KSA/Gulf data sources. Use [references/benchmarks.md](references/benchmarks.md) for industry metric comparisons. ## Phase 3: Collect + Synthesize 1. Read all analysis outputs from `artifacts/research/{slug}/` 2. Run Prompt 12 (Executive Synthesis) with all previous outputs 3. Generate final HTML report using [templates/report.html](templates/report.html) 4. Save to `artifacts/research/{date}-{slug}.html` ## Phase 4: Delivery Send the user: executive summary (3 paragraphs max), path to full HTML report, top 5 priority actions. ## Adaptive Stage Logic | Stage | Priority Analyses | Skip/Light | |-------|------------------|------------| | Idea | TAM, Personas, Competitive, Trends | Financial Model (light), Market Entry (skip) | | Startup | TAM, Competitive, Pricing, GTM, Personas | Market Entry (skip unless asked) | | Growth | Pricing, GTM, Journey, Financial, Expansion | TAM (light), Personas (light) | | Mature | SWOT, Risk, Expansion, Financial, Synthesis | TAM (skip), Personas (skip) | "Light" = include in synthesis but don't spawn a dedicated sub-agent. Use web_search inline. "Skip" = omit unless user explicitly requests. ## Artifacts - Individual analyses: `artifacts/research/{slug}/{analysis-name}.md` - Final report: `artifacts/research/{date}-{slug}.html` - Raw data: `artifacts/research/{slug}/data/` - Execution log: `data/reports.jsonl` - Feedback tracking: `data/feedback.json` ## Important Notes - Each prompt produces a consulting-grade deliverable - Use web_search to enrich with real market data; only cite verifiable sources - If user provides partial info, work with what you have and note assumptions - For Arabic output: keep brand names and technical terms in English - Prompt 12 must cross-reference insights from all previous analyses; deduplicate aggressively - Sub-agents that fail should be retried once before skipping with a note ## Reference Files | File | Contents | |------|----------| | [references/security.md](references/security.md) | Input safety, sanitization, tool constraints, artifact isolation | | [references/variable-map.md](references/variable-map.md) | Variable substitution rules and mapping table | | [references/prompts/](references/prompts/) | 12 individual analysis prompts (01-tam.md through 12-synthesis.md) | | [references/prompts.md](references/prompts.md) | Original combined prompts (backup) | | [references/gotchas.md](references/gotchas.md) | Known pitfalls and operational tips | | [references/saudi-market.md](references/saudi-market.md) | KSA/Gulf data sources and market context | | [references/benchmarks.md](references/benchmarks.md) | Industry benchmarks (SaaS, e-commerce, fintech, marketplace, mobile) | | [templates/report.html](templates/report.html) | HTML report template |

path: README.md
content: # McKinsey Research - AI Strategy Consultant Skill

Turn any AI agent into a full McKinsey-level strategy consulting team for complete market research and analysis.

## What It Does

This skill runs a full suite of consulting-grade analyses on your business:

1. **Market Sizing & TAM Analysis** - Total addressable market with top-down and bottom-up approaches
2. **Competitive Landscape** - Top 10 competitors ranked by market share, revenue, and funding
3. **Customer Personas** - 4 detailed buyer personas with psychographics and buying behavior
4. **Industry Trends** - Macro and micro trends with 5-year timeline mapping
5. **SWOT + Porter's Five Forces** - Combined strategic analysis with cross-matching
6. **Pricing Strategy** - Competitor audit, value-based pricing, and 3-tier recommendations
7. **Go-To-Market Plan** - Launch phasing, channel strategy, and KPI framework
8. **Customer Journey Mapping** - Full lifecycle from awareness to advocacy
9. **Financial Modeling** - Unit economics, 3-year projections, and break-even analysis
10. **Risk Assessment** - 15 categorized risks with scenario planning
11. **Market Entry Strategy** - Expansion analysis with 12-month roadmap
12. **Executive Strategy Synthesis** - McKinsey-style strategic recommendation

## How It Works

1. The agent asks your preferred language (Arabic or English)
2. Collects all required business information in one structured intake
3. Runs all analyses sequentially with your data
4. Delivers each analysis as a complete consulting-grade deliverable

## Installation

### Universal (Works with all platforms)

```bash
npx skills add Abdullah4AI/mckinsey-research
```

### OpenClaw

```bash
clawhub install mckinsey-research
```

Or manually:

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research ~/.openclaw/skills/
```

### Claude Code

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research ~/.claude/skills/
```

### Antigravity

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research agent/skills/
```

### Augment

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research ~/.augment/skills/
```

### Cline

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research cline/skills/
```

### CodeBuddy

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research ~/.codebuddy/skills/
```

### Command Code

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research ~/.commandcode/skills/
```

### Codex

```bash
git clone https://github.com/Abdullah4AI/mckinsey-research.git
cp -r mckinsey-research agent/skills/
```

## Usage

Just ask your AI agent for any of these:

- "Run a full market research for my business"
- "I need a competitive analysis for my product"
- "Do a McKinsey-style strategy analysis"
- "بحث سوق لمشروعي"
- "تحليل استراتيجي لمنتجي"

The skill triggers automatically and guides you through the process.

## File Structure

```
mckinsey-research/
├── SKILL.md              # Main skill instructions
├── references/
│   └── prompts.md        # The 12 strategy prompts with variables
└── README.md             # This file
```

## Credits

Built by [@Abdullah4AI](https://x.com/Abdullah4AI)

## License

MIT


path: data/feedback.json
content: {
  "reports": [],
  "schema": {
    "date": "ISO date",
    "industry": "string",
    "stage": "idea|startup|growth|mature",
    "language": "ar|en",
    "analyses_run": ["list of prompt numbers"],
    "user_revisited_sections": ["sections user asked follow-up about"],
    "total_tokens": "estimated",
    "quality_rating": "1-5 if user provided feedback"
  }
}


path: references/benchmarks.md
content: # Industry Benchmarks Reference

## SaaS
| Metric | Early Stage | Growth | Mature |
|--------|------------|--------|--------|
| CAC Payback | 12-18 months | 6-12 months | <6 months |
| LTV:CAC Ratio | 2:1 minimum | 3:1 target | 5:1+ |
| Monthly Churn | 3-5% | 1-2% | <1% |
| Net Revenue Retention | 90-100% | 100-120% | 120%+ |
| Gross Margin | 60-70% | 70-80% | 80%+ |
| ARR Growth (good) | 3x YoY | 2x YoY | 30-50% YoY |
| Rule of 40 | Aspirational | Target | Required |

## E-commerce
| Metric | Low | Average | Good |
|--------|-----|---------|------|
| Conversion Rate | 1-2% | 2-3% | 3-5% |
| Cart Abandonment | 75%+ | 65-75% | <65% |
| AOV (Saudi market) | SAR 150 | SAR 250 | SAR 400+ |
| Return Rate | 20-30% | 15-20% | <15% |
| CAC (paid) | SAR 50-100 | SAR 30-50 | <SAR 30 |

## Fintech (MENA)
| Metric | Benchmark |
|--------|-----------|
| Digital wallet adoption (KSA) | 75%+ of adults |
| Mobile payment growth | 30%+ YoY |
| BNPL default rate | 2-5% |
| Neobank CAC | $15-40 |
| Regulatory approval timeline | 6-18 months (SAMA sandbox) |

## Marketplace
| Metric | Early | Growth | Mature |
|--------|-------|--------|--------|
| Take Rate | 5-10% | 10-20% | 15-30% |
| GMV Growth | 5x+ YoY | 2-3x YoY | 30-50% YoY |
| Liquidity (fill rate) | 30-50% | 50-70% | 70%+ |
| Supply-side churn | 10-15%/mo | 5-10%/mo | <5%/mo |

## Mobile Apps
| Metric | Low | Average | Good |
|--------|-----|---------|------|
| Day 1 Retention | <25% | 25-40% | 40%+ |
| Day 30 Retention | <5% | 5-10% | 10%+ |
| Install to Signup | 30-50% | 50-70% | 70%+ |
| Free to Paid | 1-2% | 2-5% | 5%+ |
| Monthly ARPU (KSA) | $1-3 | $3-8 | $8+ |

Note: KSA/Gulf benchmarks typically show 20-30% higher ARPU than global averages for digital products due to higher purchasing power and lower market saturation.


path: references/gotchas.md
content: # Gotchas — McKinsey Research

## Sub-agent Quality
- Sub-agents return shallow analysis when the prompt is too long and unfocused. Keep each prompt under 800 words with a clear single objective.
- Batch 2 agents don't actually benefit from Batch 1 results because each sub-agent is isolated. Pass key findings from Batch 1 as context summaries (not full reports) into Batch 2 prompts.
- Sub-agents that fail silently produce empty or template-like output. Always validate output length (minimum 500 words per analysis).

## Data Quality
- TAM numbers from web_search are often 2-3 years old. Always note the source date and adjust with CAGR.
- The Saudi/Gulf market has limited English-language data online. Use Arabic search queries alongside English ones. Key sources: GASTAT, CMA, SAMA, Monsha'at reports.
- Competitor data for MENA startups is sparse. Crunchbase and MAGNiTT are better sources than generic web search.
- Financial projections without real unit economics are fiction. If user doesn't provide cost structure, flag assumptions prominently rather than inventing numbers.

## Report Quality
- The final synthesis (Prompt 12) tends to repeat the same insights across 3-4 sections. Deduplicate aggressively and cross-reference sections instead.
- Executive summaries that exceed 3 paragraphs defeat their purpose. Enforce strict length limits.
- Arabic reports with mixed English brand names need consistent formatting. Keep brand names, technical terms, and metrics in English; narrative in Arabic.

## User Input
- Vague product descriptions lead to generic analysis across all 12 prompts. If description is under 50 words, ask for clarification before proceeding.
- Users at "idea stage" don't benefit from Financial Model or detailed Pricing analysis. Adapt scope to company stage.
- Users often skip optional fields. The analysis quality drops significantly without pricing and cost structure data. Nudge for these specifically.

## Execution
- Running all 12 analyses for every request wastes tokens. Adapt based on company stage (see SKILL.md Adaptive Stage Logic).
- Web search rate limits can hit when 4+ sub-agents search simultaneously. Stagger Batch 1 launches by 5 seconds.
- HTML report generation can fail if any section contains unescaped characters. Sanitize all sub-agent outputs before assembly.


path: references/prompts/01-tam.md
content: # Prompt 1: Market Sizing & TAM Analysis
**Batch 1** (parallel, no dependencies)

You are a McKinsey-level market analyst. I need a Total Addressable Market (TAM) analysis for <user_data field="industry_product">{INDUSTRY_PRODUCT}</user_data>. Please provide:
• Top-down approach: Start from global market → narrow to my segment
• Bottom-up approach: Calculate from unit economics × potential customers
• TAM, SAM, SOM breakdown with dollar figures
• Growth rate projections for the next 5 years (CAGR)
• Key assumptions behind each estimate
• Comparison to 3 analyst reports or market research firms
Format as an investor-ready market sizing slide with clear methodology.
Context: My product is <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>, targeting <user_data field="target_customer">{TARGET_CUSTOMER}</user_data> in <user_data field="geography">{GEOGRAPHY}</user_data>.


path: references/prompts/02-competitive.md
content: # Prompt 2: Competitive Landscape Deep Dive
**Batch 1** (parallel, no dependencies)

You are a senior strategy consultant at Bain & Company. I need a complete competitive landscape analysis for <user_data field="industry">{INDUSTRY}</user_data>. Please provide:
• Direct competitors: Top 10 players ranked by market share, revenue, and funding
• Indirect competitors: 5 adjacent companies that could enter this market
• For each competitor, analyze: pricing model, key features, target audience, strengths, weaknesses, and recent strategic moves
• Market positioning map (price vs. value matrix)
• Competitive moats: What makes each player defensible
• White space analysis: Gaps no competitor is filling
• Threat assessment: Rate each competitor (low/medium/high threat)
Format as a structured competitive intelligence report with comparison tables.
My company: <user_data field="business_positioning">{BUSINESS_POSITIONING}</user_data>


path: references/prompts/03-personas.md
content: # Prompt 3: Customer Persona & Segmentation
**Batch 1** (parallel, no dependencies)

You are a world-class consumer research expert. I need deep customer personas for <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>. Please build 4 detailed personas, each with:
• Demographics: Age, income, education, location, job title
• Psychographics: Values, beliefs, lifestyle, personality traits
• Pain points: Top 5 frustrations they experience daily
• Goals & aspirations: What does success look like for them
• Buying behavior: How they discover, evaluate, and purchase products
• Media consumption: Where they spend time online and offline
• Objections: Top 3 reasons they'd say no to my product
• Trigger events: What moment makes them actively search for a solution
• Willingness to pay: Price sensitivity analysis per segment
Also provide: Segment sizing (% of total market) and prioritization matrix.
My product: <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data> in <user_data field="industry">{INDUSTRY}</user_data>


path: references/prompts/04-trends.md
content: # Prompt 4: Industry Trend Analysis
**Batch 1** (parallel, no dependencies)

You are a senior analyst at Goldman Sachs Research. I need a comprehensive trend report for the <user_data field="industry">{INDUSTRY}</user_data> sector. Please provide:
• Macro trends: 5 global forces shaping this industry (economic, regulatory, technological, social, environmental)
• Micro trends: 7 emerging patterns within the industry from the last 12 months
• Technology disruptions: What new tech is changing the game and when it will hit mainstream
• Regulatory shifts: Upcoming legislation or policy changes to watch
• Consumer behavior changes: How buyer preferences are evolving
• Investment signals: Where smart money is flowing (VC deals, M&A, IPOs)
• Timeline: Map each trend to short-term (0-1yr), mid-term (1-3yr), and long-term (3-5yr)
• "So what" analysis: What each trend means for a company like mine
Format as a trend intelligence brief with impact ratings (1-10) for each trend.
My company operates in: <user_data field="business_positioning">{BUSINESS_POSITIONING}</user_data>


path: references/prompts/05-swot-porter.md
content: # Prompt 5: SWOT + Porter's Five Forces
**Batch 2** (parallel, benefits from Batch 1 context)

You are a Harvard Business School strategy professor. I need a combined SWOT and Porter's Five Forces analysis for <user_data field="business_positioning">{BUSINESS_POSITIONING}</user_data>. For SWOT, provide:
• Strengths: 7 internal advantages with evidence
• Weaknesses: 7 internal limitations with honest assessment
• Opportunities: 7 external factors we can exploit
• Threats: 7 external factors that could harm us
• Cross-analysis: Match strengths to opportunities (SO strategy) and identify threat-weakness combos (WT risks)
For Porter's Five Forces, analyze:
• Supplier power: Who are our key suppliers and how much leverage do they have
• Buyer power: How much negotiating power do our customers have
• Competitive rivalry: How intense is competition and what drives it
• Threat of substitution: What alternatives exist beyond direct competitors
• Threat of new entry: How easy is it for new players to enter
Rate each force (1-10) and provide overall industry attractiveness score.
My business: <user_data field="full_context">{FULL_CONTEXT}</user_data>


path: references/prompts/06-pricing.md
content: # Prompt 6: Pricing Strategy Analysis
**Batch 2** (parallel, benefits from Batch 1 context)

You are a pricing strategy consultant who has worked with Fortune 500 companies. I need a comprehensive pricing analysis for <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>. Please provide:
• Competitor pricing audit: Map all competitor prices, tiers, and packaging
• Value-based pricing model: Calculate price based on customer value delivered
• Cost-plus analysis: Determine floor price from cost structure
• Price elasticity estimate: How sensitive is demand to price changes
• Psychological pricing tactics: Anchoring, charm pricing, and decoy strategies
• Tiering recommendation: Design 3 pricing tiers with feature allocation
• Discount strategy: When to discount, how much, and for whom
• Revenue projection: Model 3 pricing scenarios (aggressive, moderate, conservative)
• Monetization opportunities: Upsells, cross-sells, usage-based pricing
Format as a pricing strategy deck with specific dollar recommendations.
My product: <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>, current price: <user_data field="current_price">{CURRENT_PRICE}</user_data>, target customer: <user_data field="target_customer">{TARGET_CUSTOMER}</user_data>, cost structure: <user_data field="cost_structure">{COST_STRUCTURE}</user_data>


path: references/prompts/07-gtm.md
content: # Prompt 7: Go-To-Market Strategy
**Batch 2** (parallel, benefits from Batch 1 context)

You are a Chief Strategy Officer who has launched 20+ products across B2B and B2C markets. I need a complete go-to-market plan for <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>. Please provide:
• Launch phasing: Pre-launch (60 days), Launch (week 1), Post-launch (90 days)
• Channel strategy: Rank the top 7 acquisition channels by expected ROI
• Messaging framework: Core value proposition, 3 supporting messages, proof points
• Content strategy: What content to create for each stage of the funnel
• Partnership opportunities: 5 strategic partners that could accelerate growth
• Budget allocation: How to split a {BUDGET} marketing budget across channels
• KPI framework: 10 metrics to track with target benchmarks
• Risk mitigation: Top 5 launch risks and contingency plans
• Quick wins: 3 tactics that can generate traction within the first 14 days
Format as an actionable GTM playbook with timelines and owners.
My product: <user_data field="product_description">{PRODUCT_DESCRIPTION}</user_data>, market: <user_data field="industry">{INDUSTRY}</user_data>, budget: <user_data field="budget">{BUDGET}</user_data>, timeline: <user_data field="timeline">{TIMELINE}</user_data>


path: templates/report.html
content: <!DOCTYPE html>
<html lang="{ar|en}" dir="{rtl|ltr}">
<head>
  <meta charset="UTF-8">
  <title>McKinsey Research: {Company/Product Name}</title>
  <style>/* Professional report styling */</style>
</head>
<body>
  <header>
    <h1>Strategic Analysis Report</h1>
    <p>Prepared by McKinsey Research AI</p>
    <p>{Date}</p>
  </header>
  <section id="executive-summary">...</section>
  <section id="market-sizing">...</section>
  <section id="competitive-landscape">...</section>
  <!-- ... all 12 sections ... -->
  <section id="recommendations">...</section>
</body>
</html>


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)