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), GitHub, YouTube, LinkedIn, and Amazon. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

[Codinit] Add token-based configuration for AI usage

Implement support for token-based configuration to control and manage AI usage, allowing definition of token limits per user, project, or environment. This ensures predictable costs and prevents overuse, with configurable limits and clear error feedback.

Original Source

@@Gerome-Elassaad | 0 pts | 12/10/2025

Add support for token-based configuration to control and manage AI usage. This feature should allow defining token limits and related settings per user, project, or environment to ensure predictable costs and prevent overuse. **Acceptance Criteria:** * Ability to configure max tokens per request and per period * Configuration can be set at project or user level * Clear error/feedback when token limits are exceeded * Defaults documented and configurable via config file or env vars This will help with cost control, reliability, and safer AI adoption across the platform.

Discussion

Loading comments...