RequestHunt is a community-driven platform that collects and curates feature requests from X (Twitter), Reddit, and GitHub. We help product teams discover what features real users are asking for, making it easier to validate product ideas and prioritize feature development based on actual user demand.

How does RequestHunt collect feature requests?

RequestHunt uses AI-powered extraction to automatically collect feature requests from social media platforms including X, Reddit, and GitHub. The platform monitors discussions, issues, and posts to identify genuine user feature requests, extracting key information like the requested feature, product mentioned, and user sentiment.

Who uses RequestHunt?

RequestHunt is used by product managers, founders, developers, and product teams who want to discover what features real users are requesting. It's particularly valuable for startups looking to validate ideas, established companies prioritizing their roadmap, and developers building products that solve real user problems.

Is RequestHunt free to use?

Yes, browsing and searching feature requests on RequestHunt is completely free. We also offer API access for developers who want to integrate feature request data into their own applications. Check our pricing page for API plan details.

How often is RequestHunt data updated?

RequestHunt continuously collects feature requests from Reddit, X (Twitter), and GitHub. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

[OpenSpec] Add an agent layer for artifact creation

Implement an agent layer that summarizes long exploratory conversations and spawns an artifact-writer agent. This agent would use existing commands (e.g., `opsx:continue`) with a clean, distilled context, avoiding context bloat from full conversation history and abandoned ideas.

Original Source

@@roeehersh | 2 pts | 1/26/2026

when you have a long exploratory conversation before formalizing a change, the full history gets passed to the command including abandoned ideas and back-and-forth. This bloats the context and can confuse the output. After exploring with the user, Claude summarizes the relevant context and spawns an artifact-writer agent. The agent uses existing commands (/opsx:continue, etc.) to create the artifact - but with clean, distilled context instead of the full conversation history. Commands stay as-is. The agent is just a context-filtering layer that delegates to them.

Discussion

Loading comments...