What platforms does RequestHunt use by default?

Reddit, X, and GitHub are used by default, with scripts you can customize to your needs.

How do I set the API key for RequestHunt?

Set REQUESTHUNT_API_KEY in ~/.zshrc (or your shell profile) and reload the environment.

Are there API rate limits I should be aware of?

Yes. Cached requests are limited to 1000 per month and realtime scraping to 500 per month.

requesthunt

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npx machina-cli add skill ReScienceLab/opc-skills/requesthunt --openclaw

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SKILL.md

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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:

export REQUESTHUNT_API_KEY="your_api_key"

Get your key from: https://requesthunt.com/settings/api

Quick Check:

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:

Research Goal: What domain/area to investigate? (e.g., AI coding assistants, project management tools)
Specific Products: Any products/competitors to focus on? (e.g., Cursor, GitHub Copilot)
Platform Preference: Which platforms to prioritize? (reddit, x, github)
Time Range: How recent should the feedback be?
Report Purpose: Product planning / competitive analysis / market research?

Step 2: Collect Data

# 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/search_requests.py "code completion" --expand --limit 50

# 3. List requests filtered by topic
python3 scripts/list_requests.py --topic "ai-tools" --limit 100

Step 3: Generate Report

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...

Commands

All commands run from the skill directory.

List Requests

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
python3 scripts/list_requests.py --sortBy top --limit 20       # Top voted

Search Requests

python3 scripts/search_requests.py "authentication" --limit 20
python3 scripts/search_requests.py "oauth" --expand            # With realtime expansion
python3 scripts/search_requests.py "API rate limit" --expand --platforms reddit,x

Get Topics

python3 scripts/get_topics.py                                  # List all topics by category

Check Usage

python3 scripts/get_usage.py                                   # View API usage stats

Scrape Topic (Realtime)

python3 scripts/scrape_topic.py "developer-tools"              # Default: reddit,x
python3 scripts/scrape_topic.py "ai-assistant" --platforms reddit,x,github

API Info

Base URL: https://requesthunt.com
Auth: Bearer token (API key)
Rate Limits:
- Cached requests: 1000/month
- Realtime requests: 500/month (scraping is expensive)
Docs: https://requesthunt.com/docs

Source

git clone https://github.com/ReScienceLab/opc-skills/blob/main/skills/requesthunt/SKILL.mdView on GitHub

Overview

RequestHunt generates comprehensive user demand research reports by collecting and analyzing feedback from Reddit, X (Twitter), and GitHub. It helps teams identify top feature requests, pain points, and market signals for product planning and competitive analysis.

How This Skill Works

The workflow follows three steps: define scope (goal, products, platforms, time range, report purpose), collect data using provided scripts to scrape topics, search requests, and list requests, then generate a structured Markdown report with findings and opportunities.

When to Use It

You want to conduct demand research or analyze user demand from real feedback
You need to find feature requests from Reddit, X, and GitHub for a product area
You’re performing competitive analysis and need user expectations relative to rivals
You want a structured demand report to share with stakeholders or for roadmapping
You plan to monitor and update demand trends by running RequestHunt queries over time

Quick Start

Step 1: Define scope (goal, products, platforms, time range, report purpose)
Step 2: Collect data using the provided scripts to scrape_topic, search_requests, and list_requests
Step 3: Generate the report and deliver a structured Markdown document with findings and opportunities

Best Practices

Clarify research goals, scope, and target products before collecting data
Prioritize platforms based on where your target users engage (Reddit, X, GitHub)
Use topic filters and a defined time range to keep data relevant
Use expansion searches sparingly to balance breadth with signal
Document methodology and cite sources in the final report for credibility

Example Use Cases

Example: AI coding assistants—aggregate top feature requests from Reddit, X, and GitHub to inform roadmap
Example: Developer tools—identify recurring pain points and unmet needs across platforms
Example: Competitive analysis—compare user expectations of Copilot vs. Cursor with source-backed findings
Example: Market demand—spot high-priority capabilities to seed upcoming releases
Example: Real-time demand monitoring—regularly scrape topics to track shifting user interest

Frequently Asked Questions

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