Charter

AI-agent readiness, scored.

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Hey Product Hunt — I’m Tashfiq, the maker of Charter. I built Charter after repeatedly seeing AI coding agents fail in repositories for reasons that were not really model failures. The repo had missing context, unclear conventions, unpinned tools, unsafe config, weak test paths, or secrets sitting somewhere an agent could easily read. The agent would still try to help — but the repo had not given it a safe environment to work in. That made me wonder: why do we have linters, test coverage, CI checks, and security scanners, but no simple number for “how ready is this repository for an AI agent?” Charter is my attempt at that number. It’s an offline CLI that scans a repo and gives it a deterministic 0–100 agent-readiness score across areas like context, secrets, MCP safety, environment, CI, testing, autonomy, and governance. No LLM in the core. No network calls. Same repo, same score, every time. The approach evolved from “maybe this should be an AI review” to the opposite: a boring, reproducible rule engine with clear fixes. I wanted something teams could trust enough to run locally, put in CI, and improve over time. I’d love feedback on the rule set especially: what checks feel useful, what feels too strict, and what’s missing for your own repos.