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Codapult Guard
Deterministic architecture checks for AI coding agents
Local-first architecture guardrails for JavaScript and TypeScript. Turn approved project rules into deterministic checks for AI-assisted changes in local workflows and CI, without replacing tests, lint, or security scanners.
AI coding agents can produce a change that compiles and passes tests while still making a codebase harder to maintain. A client component might import persistence code, a route might bypass an established auth boundary, or a new dependency might cross a layer the team deliberately kept separate.
I built Codapult Guard to make those boundaries explicit and enforceable. Guard discovers facts about a JavaScript/TypeScript repository, surfaces candidate rules and contracts, and leaves approval to the team. Once approved, those rules can be checked deterministically in local workflows and CI. Existing findings can be baselined so the gate focuses on new regressions covered by the policy.
Guard is local-first and model-agnostic. It does not call an LLM or edit source files itself. Its CLI and MCP server provide project-specific architecture context to compatible coding agents, and verification receipts record which policy and checks governed a result.
It's MIT-licensed and designed to work alongside TypeScript, ESLint/Biome, tests, and security scanners, not replace them.
I'd value feedback from people using Cursor, Claude Code, Codex, or other AI coding agents in real JS/TS repositories. Which architectural boundary is hardest to keep intact in your codebase?
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About Codapult Guard on Product Hunt
“Deterministic architecture checks for AI coding agents”
Codapult Guard was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #417 on the daily leaderboard. Local-first architecture guardrails for JavaScript and TypeScript. Turn approved project rules into deterministic checks for AI-assisted changes in local workflows and CI, without replacing tests, lint, or security scanners.
Codapult Guard was featured in Software Engineering (43.2k followers), Developer Tools (521.5k followers), Artificial Intelligence (481.6k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 260.2k products, making this a competitive space to launch in.
Who hunted Codapult Guard?
Codapult Guard was hunted by Vlad Zoff. 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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Vlad Zoff