Collect and analyze real user feedback from Reddit, X, and GitHub to generate demand research reports.
Works with
Scrapes feature requests, complaints, and questions across three platforms with filtering by topic, category, platform, and time range
Includes search with real-time expansion, topic browsing, and sorting by popularity to identify top user demands
Provides structured workflow from scope definition through data collection to formatted Markdown report generation
Rate-limited API wi
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrequesthuntExecute the skills CLI command in your project's root directory to begin installation:
Fetches requesthunt from resciencelab/opc-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate requesthunt. Access via /requesthunt in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Generate user demand research reports by collecting and analyzing real user feedback from Reddit, X (Twitter), and GitHub.
Install the CLI and authenticate:
curl -fsSL https://requesthunt.com/cli | sh
requesthunt auth login
The CLI displays a verification code and opens https://requesthunt.com/device — the human must enter the code to approve. Verify with:
requesthunt config show
Expected output contains: resolved_api_key: with a masked key value (not null).
For headless/CI environments, use a manual API key instead:
requesthunt config set-key rh_live_your_key
Get your key from: https://requesthunt.com/dashboard
Default output is TOON (Token-Oriented Object Notation) — structured and token-efficient.
Use --json for raw JSON or --human for table/key-value display.
Before collecting data, clarify with the user:
# 1. Trigger realtime scrape for the topic
requesthunt scrape start "ai-coding-assistant" --platforms reddit,x,github --depth 2
# 2. Search with expansion for more data
requesthunt search "code completion" --expand --limit 50
# 3. List requests filtered by topic
requesthunt list --topic "ai-tools" --limit 100
Analyze collected data and generate a structured Markdown report:
# [Topic] User Demand Research Report
## Overview
- Scope: ...
- Data Sources: Reddit (X), X (Y), GitHub (Z)
- Time Range: ...
## Key Findings
### 1. Top Feature Requests
| Rank | Request | Sources | Representative Quote |
|------|---------|---------|---------------------|
### 2. Pain Points Analysis
- **Pain Point A**: ...
### 3. Competitive Comparison (if specified)
| Feature | Product A | Product B | User Expectations |
### 4. Opportunities
- ...
## Methodology
Based on N real user feedbacks collected via RequestHunt...
requesthunt search "authentication" --limit 20
requesthunt search "oauth" --expand # With realtime expansion
requesthunt search "API rate limit" --expand --platforms reddit,x
requesthunt list --limit 20 # Recent requests
requesthunt list --topic "ai-tools" --limit 10 # By topic
requesthunt list --platforms reddit,github # By platform
requesthunt list --category "Developer Tools" # By category
requesthunt list --sort top --limit 20 # Top voted
requesthunt scrape start "developer-tools" --depth 1 # Default: all platforms
requesthunt scrape start "ai-assistant" --platforms reddit,x,github --depth 2
requesthunt scrape status "job_123" # Check job status
requesthunt topics # List all topics by category
requesthunt usage # View account stats
requesthunt config show # Check auth status
requesthunt auth login) or manual API keyMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
Solid pick for teams standardizing on skills: requesthunt is focused, and the summary matches what you get after install.
requesthunt has been reliable in day-to-day use. Documentation quality is above average for community skills.
requesthunt reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend requesthunt for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added requesthunt from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
requesthunt is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
requesthunt fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added requesthunt from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in requesthunt — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
requesthunt fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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