Competitive Intelligence Pipeline

You are running a comprehensive competitive intelligence pipeline. This skill turns any business idea into a complete market analysis with professional deliverables.

Overview

When triggered, you will guide the user's business idea through a 9-step pipeline, producing:

1. Strategy DOCX — Feature matrix, gap analysis, AI opportunities, target segments, marketing strategy
2. Pricing DOCX — Competitor pricing comparison, package recommendations, revenue projections
3. Tech Stack Report HTML — Competitor technologies, recommended libraries/packages, GitHub repos
4. Multi-sheet Excel — All data in structured, color-coded spreadsheets (10+ sheets)
5. Complaints HTML — Competitor weaknesses and strategic opportunities
6. Brand Suggestions HTML — 30 name ideas + color palettes based on competitor gap
7. Master Dashboard HTML — Interactive report combining ALL analysis (15+ sections)

All files go into a dedicated folder the user can browse.

IMPORTANT: Setup

Before starting, install required packages:

npm install docx --prefix /sessions/laughing-keen-darwin/.npm-global 2>/dev/null
pip install openpyxl --break-system-packages 2>/dev/null

Set NODE_PATH for all Node.js commands:

NODE_PATH=/sessions/laughing-keen-darwin/.npm-global/lib/node_modules node script.js

Step 0: Understand the Idea

First, deeply understand what the user is building:

• If they provide source code or a project folder, READ IT. Analyze the tech stack, features, modules, screens.
• If they provide a description, expand it: what features would this product have? What category is it in?
• Ask clarifying questions ONLY if the idea is truly ambiguous. If you have enough to work with, proceed.

Output a brief summary: "Here's what I understand about your product: [summary]. Let me start the competitive analysis."

Step 1: Competitor Discovery

Use web search to find competitors. Categorize them:

• Direct competitors — Same target market, similar feature set
• Partial competitors — Overlap in some features but different focus
• Adjacent competitors — Related market, could expand into your space
• Local competitors — If the idea targets a specific country/region

Rules:

• Find up to 20 competitors (if more exist, pick the top 20 by market presence)
• For each competitor, research: name, website, category, founding year, estimated users, estimated revenue, pricing tiers
• Search for social media presence: Twitter/X, LinkedIn, Instagram, YouTube, TikTok, Facebook
• Note follower counts and content frequency

Save this data mentally — you'll use it across ALL subsequent steps.

Step 2: Feature Matrix

Build a comprehensive feature comparison matrix:

1. List ALL features from ALL competitors + the user's product
2. Group features into 6-10 categories
3. Rate each: "Tam" (full), "Kismi" (partial), "Yok" (none)
4. Calculate coverage scores for each competitor
5. Identify features that are UNIQUE to the user's product (USP)
6. Identify features competitors have that the user's product lacks (Gaps)

This becomes the foundation for everything else.

Step 3: Gap Analysis & AI Opportunities

From the feature matrix:

Gap Analysis:

• List USP features (user has, no competitor has)
• List features to add (competitors have, user doesn't), with priority (High/Medium/Low) and difficulty

AI/Automation Opportunities:

• For each module/feature area, identify where AI agents or automation could add value
• Map to 3 phases: Short-term (0-3 months), Mid-term (3-6 months), Long-term (6-12 months)
• Rate impact: High/Medium/Low

Step 4: Target Market & Segments

Based on competitor analysis, identify 4-8 target customer segments:

• Segment name, market size estimate, main pain point, acquisition channels, price sensitivity, priority level

Step 5: Pricing Strategy

Research competitor pricing in detail:

• All pricing tiers, per-user vs flat vs org pricing, AI add-on costs, minimum seats
• Calculate the "total SaaS cost" a user would pay for equivalent functionality using separate tools
• Recommend 3-tier pricing (Free/Pro/Business) + optional Team add-on
• If relevant, add local pricing (PPP-adjusted for the target country)
• Build a 24-month revenue projection with conservative assumptions

Step 6: Competitor Complaints & Weaknesses

Search for complaints about each competitor:

• Trustpilot, G2, Capterra, Reddit, Twitter, forums
• Categorize by type: Performance, Pricing, UX, Support, Bugs, Missing Features, etc.
• Rate severity 1-5 per category per competitor
• Build a heatmap showing complaint density
• Map each weakness to a strategic opportunity for the user's product

Step 7: Brand & Visual Analysis

Analyze competitor brand colors and visual identity:

• Extract primary color palettes for each competitor
• Identify color "gaps" (colors not heavily used by competitors)
• Generate 30 name suggestions with rationale
• For each name, suggest a 5-color palette that differentiates from competitors

Step 8: Tech Stack & Library Analysis

This step analyzes what technologies competitors use, and recommends libraries/packages/GitHub repos for the user's project based on the detected tech stack.

8.1: Detect User's Tech Stack

From Step 0, you already know what the user is building. Identify:

• Language/Framework: Flutter/Dart, React/Next.js, Vue/Nuxt, Angular, Swift, Kotlin, Python/Django, Ruby/Rails, etc.
• Backend: Supabase, Firebase, AWS, Node.js, Go, etc.
• State Management: Riverpod, Redux, Vuex, BLoC, etc.
• Database: PostgreSQL, MongoDB, SQLite, etc.
• Other: CI/CD, testing frameworks, design systems

8.2: Research Competitor Tech Stacks

For each competitor, research what technologies they use. Search for:

• "[competitor]" tech stack or "[competitor]" built with
• "[competitor]" engineering blog
• site:stackshare.io "[competitor]" — StackShare profiles
• site:builtwith.com "[competitor]" — BuiltWith reports
• "[competitor]" github — open source repos, SDKs
• Job postings (they reveal tech stack): "[competitor]" careers engineer

For each competitor, document:

• Frontend: Framework, UI library, language
• Backend: Language, framework, cloud provider
• Database: Primary DB, caching
• AI/ML: Models, providers (OpenAI, Anthropic, etc.)
• Mobile: Native, React Native, Flutter, etc.
• UI Kit / Design System: What component library or design system they use
• Infrastructure: AWS/GCP/Azure, Kubernetes, etc.
• Notable open-source: Any OSS projects they maintain

8.2b: Research Competitor UI Kits & Design Systems

This is critical — understanding what UI kits competitors use reveals their design quality, consistency, and development speed. For each competitor:

Search patterns:

• "[competitor]" design system or "[competitor]" UI kit
• "[competitor]" component library or "[competitor]" storybook
• site:dribbble.com "[competitor]" — design showcases
• site:figma.com "[competitor]" — Figma community files
• "[competitor]" figma OR sketch OR design tokens
• View competitor's website/app source for CSS framework clues (Tailwind classes, Material UI, etc.)
• Check competitor's GitHub for design system repos: github.com/[company] design-system

For each competitor, identify:

• Component Library: Material Design, Ant Design, Chakra UI, shadcn/ui, custom, etc.
• CSS Framework: Tailwind CSS, Bootstrap, styled-components, CSS Modules, etc.
• Design System: Whether they have a public design system, Storybook, Figma kit
• Icon Set: Lucide, Heroicons, Material Icons, custom icons, etc.
• Typography: Inter, SF Pro, Roboto, custom fonts
• Color System: Material 3, custom tokens, CSS variables approach
• Dark Mode: Supported or not
• Motion/Animation: Framer Motion, Lottie, CSS animations, Rive
• Accessibility: WCAG compliance level if detectable