End-to-end competitive intelligence pipeline for any business idea. Produces a complete analysis folder: competitor research, feature matrix, gap analysis, AI opportunities, pricing strategy, complaints, brand suggestions, and interactive HTML dashboard. Use when user asks to analyze a business idea, find competitors, do competitor/market analysis, or says "rakip analizi yap", "bu fikri analiz et", "pazar araştırması". Produces DOCX reports, multi-sheet Excel, and polished HTML dashboards. Trigger for ANY competitive analysis request.

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:

Strategy DOCX — Feature matrix, gap analysis, AI opportunities, target segments, marketing strategy
Pricing DOCX — Competitor pricing comparison, package recommendations, revenue projections
Tech Stack Report HTML — Competitor technologies, recommended libraries/packages, GitHub repos
Multi-sheet Excel — All data in structured, color-coded spreadsheets (10+ sheets)
Complaints HTML — Competitor weaknesses and strategic opportunities
Brand Suggestions HTML — 30 name ideas + color palettes based on competitor gap
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:

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

8.3: Recommend Libraries & Packages

Based on the user's tech stack, research and recommend packages across these categories:

For the detected framework (e.g., Flutter):

Search patterns:

best [framework] packages for [feature] 2025 2026
[framework] [feature] library github stars
awesome-[framework] github — curated lists
pub.dev / npm / pypi / crates.io top packages for [feature]

Categories to cover:

Core Architecture — State management, routing, DI, networking
UI Kit / Component Library — Complete design system packages (THE MOST IMPORTANT CATEGORY — see 8.3b below)
UI Primitives — Buttons, inputs, dialogs, bottom sheets, navigation components
Charts & Data Viz — Chart libraries, graphs, dashboards, heatmaps
Animation & Motion — Transition libraries, Lottie, Rive, micro-interactions
Forms & Validation — Form builders, input masks, validators
Icons & Assets — Icon packs, SVG libraries, illustration sets
Data & Storage — Local DB, caching, sync, encryption
Auth & Security — Authentication, authorization, encryption
AI & ML — LLM integration, on-device ML, NLP
Media — Image processing, camera, file picker, PDF generation
Communication — Push notifications, WebSocket, email, chat
Analytics & Monitoring — Crash reporting, analytics, logging
Payment & Finance — Payment gateways, invoicing, currency
Social Media — API SDKs, sharing, deep linking
Testing — Unit, widget/component, integration, E2E
DevOps — CI/CD, code generation, linting

For EACH recommended library, document:

Name and package registry link (pub.dev, npm, pypi, etc.)
GitHub URL and star count
Weekly downloads or popularity metric
Description — what it does and why it's relevant
Maturity — Stable / Beta / Experimental
License — MIT, Apache, BSD, etc.
Recommendation level — Essential / Recommended / Optional
Which competitors use it (if known)

Also search for:

GitHub template repos / starter kits for the tech stack
Boilerplate projects that combine multiple recommended packages
Open-source competitors or similar projects on GitHub

8.3b: Recommend UI Kits & Design Systems

This is the MOST IMPORTANT library category. Based on competitor UI kit research from 8.2b and the user's tech stack, recommend complete design system packages.

Search patterns:

best [framework] UI kit 2025 2026
[framework] component library comparison
[framework] design system production ready
[framework] material design OR cupertino OR custom design system
awesome-[framework] UI — curated lists

Framework-specific UI Kit recommendations:

Flutter/Dart:

Material 3 (built-in) — Google's official design system
flutter_adaptive_scaffold — Responsive layouts
Widgetbook — Component catalog / Storybook equivalent
Forui — Fork of shadcn/ui for Flutter
Flutter Acrylic / glassmorphism — Modern glass effects
Fluent UI (fluent_ui) — Microsoft's Fluent design for Flutter
MacOS UI (macos_ui) — macOS-native look
Shadcn Flutter (shadcn_flutter) — shadcn/ui port for Flutter
GetWidget — 1000+ pre-built widgets
VelocityX — Minimalist utility framework

React/Next.js:

shadcn/ui — Copy-paste Radix+Tailwind components (55K+ stars)
Radix UI — Headless accessible primitives (14K+ stars)
MUI (Material UI) — Google Material (90K+ stars)
Ant Design — Enterprise-grade (90K+ stars)
Chakra UI — Accessible component library (36K+ stars)
Mantine — Full-featured with hooks (24K+ stars)
NextUI — Beautiful, modern (19K+ stars)
Tremor — Dashboard components (15K+ stars)
Park UI — Ark UI + design tokens
Catalyst — Tailwind Labs official UI kit

Vue/Nuxt:

Vuetify — Material Design (39K+ stars)
PrimeVue — Rich enterprise suite (7K+ stars)
Nuxt UI — Official Nuxt components (3K+ stars)
Naive UI — Comprehensive Vue 3 (15K+ stars)
Element Plus — Element for Vue 3 (23K+ stars)
Headless UI — Tailwind Labs headless (24K+ stars)

For EACH recommended UI kit, document:

Name and package registry link
GitHub URL and star count
Weekly downloads or popularity metric
Component count — How many components included
Theming — CSS variables, design tokens, theme builder
Dark mode — Built-in support or manual
Accessibility — WCAG level, ARIA support
Figma kit — Available or not
Storybook — Available or not
Bundle size — Tree-shakeable, total size
Maturity — Stable / Beta / Experimental
License — MIT, Apache, etc.
Recommendation level — Essential / Recommended / Optional
Comparison note — How it compares to what competitors use

8.4: Build Tech Stack Comparison Table

Create a comparison showing:

Technology Area	User's Product	Competitor 1	Competitor 2	...
Frontend	Flutter 3.x	React	Vue.js	...
Backend	Supabase	Custom Node.js	Django	...
AI Provider	OpenAI	OpenAI + Custom	Anthropic	...

8.5: Generate Tech Stack Report

Produce a Tech Stack Report HTML containing:

Competitor tech stack cards (what each competitor uses)
Tech stack comparison table
Recommended library cards grouped by category, with:
- Package name, description, GitHub stars, downloads
- Color-coded recommendation level (Essential=green, Recommended=blue, Optional=gray)
- Links to GitHub and package registry
Installation commands (copy-pasteable)
GitHub repos & starter kits section
Architecture diagram suggestion based on recommended stack

Also add 3 new sheets to the Excel workbook:

"Rakip Teknolojiler" (Competitor Technologies) — tech stack per competitor
"Kutuphane Onerileri" (Library Recommendations) — all recommended packages with details
"UI Kit Karsilastirma" (UI Kit Comparison) — competitor UI kits vs recommended UI kits with component count, theming, dark mode, accessibility, Figma kit, Storybook, bundle size

Step 9: Generate All Deliverables

Now produce all the files. Read the generation scripts from this skill's scripts/ directory:

File Generation Order:

Create output folder:

mkdir -p "[OUTPUT_DIR]/[ProductName]_Competitive_Analysis"

Generate Strategy DOCX — Read and customize scripts/generate_strategy_docx.js
- Populate with YOUR researched data (features, competitors, gaps, AI opportunities, segments, marketing)
- Run with NODE_PATH set
Generate Pricing DOCX — Read and customize scripts/generate_pricing_docx.js
- Populate with YOUR pricing data, packages, Turkey/local pricing, revenue projections
Generate Excel workbook — Read and customize scripts/generate_excel.py
- Creates 10+ sheets: Feature Matrix, AI Opportunities, Target Segments, Gap Analysis, Competitor Pricing, Package Details, Local Pricing, Revenue Projection, Competitor Technologies, Library Recommendations
Generate Tech Stack Report HTML — Build a self-contained HTML file with:
- Competitor tech stack cards
- Tech stack comparison table
- Recommended library cards (grouped by category, with GitHub stars, links, install commands)
- Architecture suggestion section
Generate Complaints HTML — Build a self-contained HTML file with:
- Complaint cards per competitor with severity badges
- Heatmap table (complaint categories × competitors)
- Strategy cards showing how to exploit each weakness
Generate Brand Suggestions HTML — Build an HTML file with:
- Competitor color swatches
- Color gap analysis
- 30 name cards with color palettes
Generate Master Dashboard HTML — The crown jewel. A single interactive HTML file with:
- Dark theme (use emerald/green as default, or match user's brand)
- Fixed navigation with section links
- Hero with key stats (competitor count, feature count, AI opportunities, etc.)
- All analysis sections: Competitor overview, Feature matrix, Competitor details with tabs, Gap analysis, AI opportunities with phase filter, Target segments, Pricing comparison, Package recommendations, Local pricing, Revenue projection, Tech stack comparison, Recommended libraries, Social media strategy, Brand analysis, Process summary
- All data embedded in JavaScript variables — no external dependencies

Script Customization Pattern

The scripts in scripts/ are TEMPLATES. For each one:

Read the script
Replace the data arrays/objects with YOUR researched data
Replace product name, colors, dates
Write the customized version to a temp location
Execute it

Output Structure

[ProductName]_Competitive_Analysis/
├── [ProductName]_Strategy_Report.docx        # Feature matrix, gaps, AI, segments, marketing
├── [ProductName]_Pricing_Report.docx         # Pricing analysis, packages, revenue projection
├── [ProductName]_Detailed_Analysis.xlsx      # 10+ sheets with all structured data
├── [ProductName]_Tech_Stack_Report.html      # Competitor tech stacks + recommended libraries
├── [ProductName]_Competitor_Complaints.html  # Weakness analysis + strategic opportunities
├── [ProductName]_Brand_Suggestions.html      # 30 names + color palettes
└── [ProductName]_Master_Dashboard.html       # Interactive HTML combining EVERYTHING

Language

If the user writes in Turkish, produce ALL reports in Turkish
If the user writes in English, produce ALL reports in English
Match the user's language throughout

Quality Standards

Feature matrix must have 30-50 features minimum
At least 5 competitors researched in depth (up to 20)
AI opportunities: minimum 15 identified
Complaints: search at least 3 review sources per competitor
HTML reports must be fully self-contained (no external dependencies except CDN fonts)
Excel must have color-coded cells, frozen panes, proper column widths
DOCX must have cover page, headers/footers, page numbers, professional tables

Web Search Strategy

For each competitor, search for:

"[competitor name]" pricing plans 2025 2026 — for pricing data
"[competitor name]" features list — for feature discovery
"[competitor name]" complaints OR reviews site:reddit.com OR site:trustpilot.com OR site:g2.com — for weaknesses
"[competitor name]" users OR revenue OR funding — for market data
"[competitor name]" social media — for SM presence
"[competitor name]" tech stack OR built with OR engineering blog — for technology detection
site:stackshare.io "[competitor name]" — StackShare profiles
"[competitor name]" careers engineer — job postings reveal tech stack

For library research: 9. best [framework] packages [category] 2025 2026 — package recommendations 10. awesome-[framework] github — curated package lists 11. [framework] [feature] library github stars — popular libraries 12. [framework] starter kit OR boilerplate OR template — starter projects

Error Handling

If a web search fails, try alternative queries
If a specific competitor has limited data, note it and move on
If npm/pip install fails, try alternative installation methods
Always validate generated files exist and have reasonable size before presenting to user

Final Presentation

After generating all files:

List all generated files with computer:// links
Show a brief summary of key findings (3-5 bullet points)
Highlight the most interesting strategic opportunities
The Master Dashboard HTML should be presented as the primary deliverable

competitive-intelligence