Open Prompt Hub – Don't share code, share intent
GitHub for prompts is an interesting bet, but PromptBase and FlowGPT already exist.

GitHub for prompts with security scans, but FlowGPT already owns this category.
Prompt engineers, AI developers
FlowGPT · PromptBase
How it Works:
Instead of shipping binaries or source code, you share instructions and specs in form of a prompt. You can take this prompt, paste it into their agent or IDE and watch it build. If it’s not a perfect fit? Fork it, tweak it, and generate your custom version.
All meta infos like version, description, test cases etc. are stored in a frontmatter block at the start of the prompt. So it's one file containing all the infos you need. (https://openprompthub.io/docs)
Features of the platform: - Versioned prompts with infos which models to best use - Forking for customization - Security Scans: prompts are scanned for security issues and prompt injections. - User can give feedback, if the prompt successfully build what was promissed (scoped on models, so you know which one to best use for execution) - Flagging mechanism
It’s an MVP, but the core features—versioning, model-specific build status, and security scanning — are live.
I'm currently looking into further features, such as: - a git-like cli for publishing prompts and downloading/piping them directly to your agent - multi stage/file prompts for more complex applications - configurable prompts for e.g. switching programming languages, features, etc. - better spec and test definition for build verification
I’d love your feedback... on the idea, the spec and the platform.
GitHub for prompts is an interesting bet, but PromptBase and FlowGPT already exist.
GitHub for prompts, but prompt registries already exist and CLI features aren't live yet.
GitHub for prompts, but PromptBase and countless repos already do this.
Static prompt directory, but every major AI tool has a free prompt library now.
Local prompt storage when ChatGPT history and pinned messages already exist.
Git for AI prompts, but missing actual code tracking and ecosystem adoption.