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policyctl
Provider-agnostic policy runtime for coding agents
PolicyCtl is a provider-agnostic policy runtime for AI coding agents. It enforces rules deterministically before actions execute, instead of relying on prompt instructions. One `.policyctl.yml` policy works across Claude Code, Cursor, OpenAI Codex, and CI, with sub-12ms local evaluation, pre-execution blocking, secret detection, policy-file protection, and native hook generation.
AI coding agents can write, delete, and execute code faster than you can review every action.
That is exactly why I built PolicyCtl.
PolicyCtl is a deterministic policy runtime that sits between your coding agent and your codebase, enforcing hard rules before actions execute. Define your policies once in `.policyctl.yml` and enforce them across Claude Code, Cursor, Codex, and CI.
Block secrets. Protect critical files. Restrict dangerous commands. Require tests. Let agents move quickly within boundaries you control.
Built for the point where AI agents stop being autocomplete and start becoming autonomous engineers.
What should your coding agent never be allowed to do?
Quick launch story: this started as a weekend hack after my coding agent rewrote a migration file that my instructions explicitly said (three messages earlier!) not to touch. Prompts are advice; advice degrades as context fills up. So I built a runtime instead — one YAML file compiled to pattern tables, enforced at the agent's tool-call layer before files hit disk. Under 12ms per call, no LLM in the decision path, 100% local.
Free, MIT, local-first — try it in 30 seconds: npx @policyctl/cli init
Ask me anything about the matcher design (file, command, diff, AST, regex, glob, tool, semantic) — genuinely my favorite part of this project.
About policyctl on Product Hunt
“Provider-agnostic policy runtime for coding agents”
policyctl was submitted on Product Hunt and earned 2 upvotes and 2 comments, placing #122 on the daily leaderboard. PolicyCtl is a provider-agnostic policy runtime for AI coding agents. It enforces rules deterministically before actions execute, instead of relying on prompt instructions. One `.policyctl.yml` policy works across Claude Code, Cursor, OpenAI Codex, and CI, with sub-12ms local evaluation, pre-execution blocking, secret detection, policy-file protection, and native hook generation.
policyctl was featured in Open Source (68.8k followers), Developer Tools (519.7k followers), Artificial Intelligence (479k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 252k products, making this a competitive space to launch in.
Who hunted policyctl?
policyctl was hunted by Roshan Ravani Singh. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Roshan Ravani Singh