requesthunt_skill
- Python
472
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill resciencelab/opc-skills --skill requesthunt- SKILL.md3.7 KB
Overview
This skill generates user demand research reports by scraping and analyzing real user feedback from Reddit, X, and GitHub. It converts feature requests, complaints, and questions into structured insights that inform product planning, competitive analysis, and roadmap prioritization. The output is a clear, actionable report with ranked requests, pain-point analysis, and opportunity recommendations.
How this skill works
You define the research scope (goal, target products, platforms, time range) and run targeted scrapes and searches to collect live and cached user feedback. The skill aggregates requests, expands searches to related phrases, and ranks results by volume or votes. It then synthesizes findings into a structured report with top feature requests, pain points, comparative analysis, and suggested opportunities.
When to use it
- Validating demand for a proposed feature before development
- Discovering high-frequency complaints and unmet needs in your niche
- Competitive benchmarking to see what users ask from rival products
- Market research for product-market fit or prioritization
- Ongoing monitoring of user sentiment across Reddit, X, and GitHub
Best practices
- Start with a clearly scoped research question and target products or topics
- Combine realtime scrapes with cached searches to balance freshness and rate limits
- Use search expansion to capture synonyms and related phrases for broader coverage
- Prioritize results by source credibility and cross-platform frequency, not just volume
- Set a reasonable time window to focus on relevant, actionable feedback
Example use cases
- Map the top 10 feature requests for an AI coding assistant to prioritize roadmap items
- Identify recurring authentication and OAuth pain points across developer communities
- Compare user expectations for competing project management tools to inform positioning
- Produce a one-page demand brief for investors or stakeholders ahead of a demo
- Monitor emerging requests to spot product opportunities before competitors
FAQ
Reddit, X (Twitter), and GitHub are the primary sources for scraping and analysis.
How fresh is the data and are there rate limits?
You can run realtime scrapes for current feedback, but realtime and cached queries are subject to monthly rate limits—balance realtime scraping with cached searches to conserve quota.
