Agent skill

requesthunt

Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, and GitHub.

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill requesthunt-resciencelab-opc-skills --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 4 KB
Bundled scripts: none
Path: skills/analysis/requesthunt-resciencelab-opc-skills/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# RequestHunt Skill Generate user demand research reports by collecting and analyzing real user feedback from Reddit, X (Twitter), and GitHub. ## Prerequisites Set API key in `~/.zshrc`: ```bash export REQUESTHUNT_API_KEY="your_api_key" ``` Get your key from: https://requesthunt.com/settings/api **Quick Check**: ```bash cd <skill_directory> python3 scripts/get_usage.py ``` ## Research Workflow This skill helps you generate comprehensive user demand research reports. Follow this workflow: ### Step 1: Define Scope Before collecting data, clarify with the user: 1. **Research Goal**: What domain/area to investigate? (e.g., AI coding assistants, project management tools) 2. **Specific Products**: Any products/competitors to focus on? (e.g., Cursor, GitHub Copilot) 3. **Platform Preference**: Which platforms to prioritize? (reddit, x, github) 4. **Time Range**: How recent should the feedback be? 5. **Report Purpose**: Product planning / competitive analysis / market research? ### Step 2: Collect Data ```bash # 1. Trigger realtime scrape for the topic python3 scripts/scrape_topic.py "ai-coding-assistant" --platforms reddit,x,github # 2. Search with expansion for more data python3 scripts/

What's inside
Steps it walks through
  1. Prerequisites
  2. Research Workflow
  3. Step 1: Define Scope
  4. Step 2: Collect Data
  5. Step 3: Generate Report
  6. Commands
  7. List Requests
  8. Search Requests
  9. Get Topics
  10. Check Usage
  11. Scrape Topic (Realtime)
  12. API Info
Ships with 1 file
  • metadata.json
Commands it runs
export REQUESTHUNT_API_KEY="your_api_key"
cd <skill_directory>
python3 scripts/get_usage.py
python3 scripts/scrape_topic.py "ai-coding-assistant" --platforms reddit,x,github
python3 scripts/search_requests.py "code completion" --expand --limit 50
python3 scripts/list_requests.py --topic "ai-tools" --limit 100
python3 scripts/list_requests.py --limit 20                    # Recent requests
python3 scripts/list_requests.py --topic "ai-tools" --limit 10 # By topic
python3 scripts/list_requests.py --platforms reddit,github     # By platform
python3 scripts/list_requests.py --category "Developer Tools"  # By category
More from claude-skill-registry
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About this skill
What does the requesthunt skill do?

Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, and GitHub.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill requesthunt-resciencelab-opc-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going