io.github.get-tmonier/argot

Your codebase has a voice. argot makes AI code speak it.
AI writes the code. argot harnesses it with the one thing that can't hallucinate: your repo's own history. Statistics, not a second LLM — flagging a dependency you've never used, a function you already wrote, an import that breaks your layering, a test quietly weakened, a convention only your team knows. 100% local, replayable.

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🎬 Watch the 45-second launch film

Type checkers ask "is this valid?" argot asks the question that used to live in code review: "is this how we do it here?" — and catches AI code that's flawless, type-correct, lint-clean, and still doesn't belong. It answers with statistics on your repo's own history — the statistical core deterministic and replayable, everything local — never a second LLM judging the first.

It also asks a second question no other tool asks: did the AI play fair? When an agent can't make a failing test pass, the cheapest path to "done" is to make the test stop looking. argot reads both sides of every diff and pairs a weakened, disabled, or deleted test with the production change it covers.

Five learned detectors — plus the rules only your repo could write

The first five are learned from your git history. The sixth is written by you — and it's the

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