ContinuityGuard

What is ContinuityGuard, and why does it exist

ContinuityGuard is a free, open-source, local-first CLI. It ingests a directory of already-generated video clips from any AI short-drama pipeline, decodes them withffmpeg, and runs two scoring passes: a character-consistency check (cosine similarity between MobileNetV2 embeddings of same-named-character crops across shots, best-validated on photorealistic content and unverified on stylized or anime-adjacent designs) and a physics-plausibility heuristic (frame-to-frame diff ratios against a shot's own local motion baseline, a heuristic that flags shots for human review rather than a physics simulator). It writes both a human-readable terminal report and a machine-readable JSON report, and it never makes a network call while doing any of it.

It exists because AI short-drama generation is shipping hundreds of new titles a day, and every one of those titles is assembled from many separately generated shots. Generation models drift: character faces shift slightly between cuts, and motion sometimes jumps in a way that reads as physically wrong the moment a human watches it. Catching that before a re-render saves the cost of redoing the shot from scratch.

ContinuityGuard is a QA layer, not a generator, and that is the point. It sits on top of whatever pipeline already produced your footage instead of locking you into one, it runs entirely on your own machine so unreleased footage never has to leave it, and it is free with no account or API key required. A generation platform's own built-in QA, if it has one, only ever sees its own output; ContinuityGuard works the same way whether your clips came from an open-source pipeline, a commercial one, or a mix of both on the same project.

Your unreleased footage never leaves your machine. Every clip is decoded locally viaffmpeg, every embedding is computed locally via a bundled offline ONNX model, and the report is written to a local file. No account, no API key, no upload step, for any frame.npm run verify:zero-networkproves this empirically: it monkey-patches every network entry point Node exposes and runs a real scan against this repo's own fixtures, and it would fail loudly if anything tried to reach the network. It runs in CI on every push. SeeCHANGELOG.mdfor the exact result.

Is this validated for anime or stylized AI-generated characters?No. Character-consistency scoring is best-validated on photorealistic content. Its accuracy on stylized or anime-adjacent designs, which is most short-drama content, has not been independently benchmarked yet. Treat every flag on stylized footage as a prompt to look closer. This is the single most important caveat in this repo; see "Known limitations" above.

Does the physics check actually understand physics?No. It's a frame-to-frame motion-discontinuity heuristic. It compares each shot's frame-to-frame diffs against that shot's own local baseline and flags outliers for human review, with no attempt to model real-world physics. It will produce false positives on legitimate fast motion or stylized jump-cuts, and false negatives on subtle implausible motion that stays under the threshold.

Do I need a GPU?No. Everything runs on CPU viaonnxruntime-node, using a small (14MB) MobileNetV2 model. The 8-clip fixture scan above completes in under two seconds on an ordinary laptop.

Does this upload my clips anywhere?No. That's mechanically enforced:npm run verify:zero-networkpatches every network entry point Node exposes and runs a real scan, and the check fails loudly if anything tries to reach the network. It runs on every CI push.

Why do I need to install ffmpeg separately instead of it being bundled?A bundled static ffmpeg binary would add tens of megabytes per platform to this package and would inherit ffmpeg's own licensing terms, which shift between LGPL and GPL depending on which codecs are compiled in. ffmpeg is close to ubiquitous on developer machines already, so ContinuityGuard depends on a system install and checks for it at startup with a clear, OS-specific error if it's missing.

Is this on npm yet?Yes.npm install -g continuityguard-cliinstalls it today. The Python package is also on PyPI (pip install continuityguard-cli), using the same scoring logic and the same bundled model -- seepython/README.md.

- docs/getting-started.md-- install paths for both packages, your first scan, the library API.
- docs/concepts.md-- what CG01-CG04 each do, and where the 0.88 / 3x thresholds came from.
- docs/integrations/ci.md-- wiring ContinuityGuard into a CI pipeline.
- python/README.md-- the Python package's own README (PyPI quickstart, CLI reference, fidelity notes).

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