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feat(requesthunt): add platform selection guide (v2.2.0) (#74)
- Add data-driven Platform Selection Guide based on 220+ topic research - Platform strengths table, category recommendations, quick selection rules - Category-aware scraping strategies in workflow examples - Enhanced report template with platform signal comparison
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CHANGELOG.md

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| Skill | Current Version | Requires | Min Versions |
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|-------|-----------------|----------|--------------|
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| **requesthunt** | 2.1.0 | - | - |
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| **requesthunt** | 2.2.0 | - | - |
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| **domain-hunter** | 1.0.0 | twitter, reddit | twitter ≥1.0.0, reddit ≥1.0.0 |
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| **logo-creator** | 1.0.0 | nanobanana | nanobanana ≥1.0.0 |
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| **banner-creator** | 1.0.0 | nanobanana | nanobanana ≥1.0.0 |
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## [Unreleased]
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### requesthunt
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- **Version**: 2.1.0 → 2.2.0
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- Added **Platform Selection Guide** with data-driven recommendations based on research across 220+ topics and 9 product categories
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- Platform × category matrix covering automotive, gaming, travel, food, health, real estate, social, creator economy, and developer tools
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- Quick selection rules for choosing optimal platforms per product type
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- Updated research workflow with category-aware scraping strategies (YouTube-first for consumer, Reddit-first for dev tools, LinkedIn-first for B2B)
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- Enhanced report template with platform signal comparison table and platform strategy section
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## Released Versions
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## [1.2.0] - 2026-04-15

skills.json

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},
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{
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"name": "requesthunt",
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"version": "2.1.0",
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"version": "2.2.0",
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"description": "Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, and LinkedIn.",
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"logo": "https://raw.githubusercontent.com/ReScienceLab/opc-skills/main/skill-logos/requesthunt.svg",
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"icon": "globe",

skills/requesthunt/SKILL.md

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Default output is TOON (Token-Oriented Object Notation) — structured and token-efficient.
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Use `--json` for raw JSON or `--human` for table/key-value display.
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## Platform Selection Guide
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Each platform captures different types of user feedback. Choose platforms based on the product category to maximize signal quality.
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### Platform Strengths
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| Platform | Best For | Signal Type | Typical Yield |
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|----------|----------|-------------|---------------|
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| **YouTube** | Consumer products, hardware, lifestyle apps | Specific feature asks from review/tutorial comments | High (10-29 per topic) |
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| **Reddit** | Developer tools, creator economy, niche communities | Deep technical discussions, long-tail needs | High for dev topics (up to 176) |
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| **LinkedIn** | B2B software, healthcare, enterprise tools | Professional/industry opinions, market context | Low volume but high engagement |
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| **X** | Trending topics, quick sentiment signals | Fragmented feedback, emotional reactions | Low-medium (1-6 per topic) |
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| **GitHub** | Open-source tools, developer infrastructure | Concrete bugs and feature requests from issues | High for OSS, zero for non-tech |
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### Recommended Platforms by Category
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| Category | Primary | Secondary | Notes |
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|----------|---------|-----------|-------|
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| **Automotive / Hardware** | YouTube | Reddit | Video review comments are the richest source (dashcams: 29, EVs: 19) |
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| **Gaming / Entertainment** | YouTube | Reddit | Game streams and reviews generate natural feedback |
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| **Travel / Transportation** | YouTube | LinkedIn | Travel vlogs + LinkedIn for business travel needs |
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| **Social / Communication** | YouTube | Reddit | App review videos + community discussions |
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| **Food / Dining** | YouTube | Reddit | Recipe and delivery app review comments |
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| **Real Estate / Home** | YouTube | X | Interior design and renovation videos dominate |
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| **Education / Learning** | YouTube || Tutorial video comments are the only reliable source |
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| **Health / Medical** | LinkedIn | X | Rare LinkedIn-dominant category (professional healthcare) |
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| **Creator Economy** | Reddit | GitHub | Reddit communities overwhelmingly active (Newsletter: 176 requests) |
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| **Developer Tools** | Reddit | GitHub | Technical communities + open-source issue trackers |
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| **AI / SaaS Products** | Reddit | LinkedIn | Reddit for user complaints, LinkedIn for industry analysis |
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### Quick Selection Rules
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- **Consumer / hardware / lifestyle** → YouTube first, Reddit second
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- **Developer / creator tools** → Reddit first, GitHub second
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- **B2B / enterprise / medical** → LinkedIn first, X second
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- **Has open-source projects** → add GitHub
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- **Everything** → add X as a supplementary source
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## Research Workflow
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### Step 1: Define Scope
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Before collecting data, clarify with the user:
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1. **Research Goal**: What domain/area to investigate? (e.g., AI coding assistants, project management tools)
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2. **Specific Products**: Any products/competitors to focus on? (e.g., Cursor, GitHub Copilot)
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3. **Platform Preference**: Which platforms to prioritize? (reddit, x, github, youtube, linkedin)
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1. **Research Goal**: What domain/area to investigate?
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2. **Specific Products**: Any products/competitors to focus on?
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3. **Platform Selection**: Use the guide above to pick 2-3 best platforms for the category
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4. **Time Range**: How recent should the feedback be?
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5. **Report Purpose**: Product planning / competitive analysis / market research?
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### Step 2: Collect Data
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Choose platforms strategically based on the category:
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```bash
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# 1. Trigger realtime scrape for the topic
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requesthunt scrape start "ai-coding-assistant" --platforms reddit,x,github,youtube,linkedin --depth 2
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# Consumer hardware — YouTube-first strategy
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requesthunt scrape start "smart home devices" --platforms youtube,reddit --depth 2
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# Developer tools — Reddit-first strategy
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requesthunt scrape start "code editors" --platforms reddit,github --depth 2
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# 2. Search with expansion for more data
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requesthunt search "code completion" --expand --limit 50
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# B2B / enterprise — LinkedIn-first strategy
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requesthunt scrape start "electronic health records" --platforms linkedin,x --depth 2
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# 3. List requests filtered by topic
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# Broad research — all platforms
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requesthunt scrape start "AI coding assistants" --platforms reddit,x,github,youtube,linkedin --depth 2
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# Search with expansion for more data
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requesthunt search "dark mode" --expand --limit 50
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# List requests filtered by topic
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requesthunt list --topic "ai-tools" --limit 100
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```
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## Overview
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- Scope: ...
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- Data Sources: Reddit (X), X (Y), GitHub (Z), YouTube (W), LinkedIn (V)
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- Data Sources: Reddit (N), X (N), GitHub (N), YouTube (N), LinkedIn (N)
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- Platform Strategy: [why these platforms were chosen for this category]
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- Time Range: ...
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## Key Findings
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### 1. Top Feature Requests
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| Rank | Request | Sources | Representative Quote |
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|------|---------|---------|---------------------|
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| Rank | Request | Platform | Votes | Representative Quote |
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|------|---------|----------|-------|---------------------|
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### 2. Pain Points Analysis
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- **Pain Point A**: ...
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- Sources: [which platforms surfaced this]
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### 3. Platform Signal Comparison
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| Insight | Reddit | YouTube | LinkedIn | X | GitHub |
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|---------|--------|---------|----------|---|--------|
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| Volume | ... | ... | ... | ... | ... |
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| Signal type | Technical | UX/Feature | Strategic | Sentiment | Bug/FR |
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### 3. Competitive Comparison (if specified)
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### 4. Competitive Comparison (if specified)
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| Feature | Product A | Product B | User Expectations |
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### 4. Opportunities
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### 5. Opportunities
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- ...
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## Methodology
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Based on N real user feedbacks collected via RequestHunt...
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Based on N real user feedbacks collected via RequestHunt from [platforms]...
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```
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## Commands
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```bash
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requesthunt list --limit 20 # Recent requests
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requesthunt list --topic "ai-tools" --limit 10 # By topic
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requesthunt list --platforms reddit,github,youtube # By platform
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requesthunt list --platforms reddit,github,youtube # By platform
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requesthunt list --category "Developer Tools" # By category
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requesthunt list --sort top --limit 20 # Top voted
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```

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