Airuncode
Freemium
Developers preferring fully local agent execution
Every week you spend thirty seconds on a PR that turns out to be pure LLM output — polished title, confident summary, zero grasp of your codebase — and you cannot just close it on suspicion without burning the one real first-timer in the batch. SlopGuard scores every incoming PR and issue against heuristics, labels the likely machine-made ones with the specific reasons, and leaves the close button entirely in your hands.
The tool installs as a GitHub App with no Action YAML, no CI config, and no secrets to wire. Each contribution gets a 0–100 slop score derived from heuristics only — no LLM API calls — and at or above your configured threshold it adds a quarantine label plus a review comment listing the exact signals, such as leaked chat-assistant phrases or prompt fingerprints. Below the threshold it stays silent. You reply with slash commands to approve, reject, or flag a false positive. The vendor states the golden-set benchmark sits at 100% precision and 92% recall — every flagged item was real slop, and the single miss was slop that slipped through, not a genuine contributor wrongly quarantined.
Bottom line: Pick this if you are an open-source maintainer drowning in AI-generated PRs and need triage help that will never auto-close a real contributor; skip it if your team needs programmatic API access, self-hosted deployment outside the Commons Clause terms, or detection that adapts beyond static heuristics as generation patterns shift.
For individuals and public repos. Forever free.
For maintainers with private repos and higher limits.
For orgs that need visibility, alerting, and controls.
For companies that need SSO, audit export, and priority support.
View full pricing on github.com →
Pricing may have changed since last verified. Check the official site for current plans.
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Freemium
Developers preferring fully local agent execution
Freemium
Engineering teams needing private/local AI coding assistance
SlopGuard sits between your GitHub inbox and your review queue. When a PR or issue arrives, the app scores it against a heuristic ruleset — looking for leaked chat-assistant boilerplate, prompt fingerprints, generic auto-generated titles, and empty descriptions — and returns a 0–100 slop score with the specific signals attached. At or above the threshold you configure, it labels the contribution and leaves a review comment. Below it, nothing happens. You respond via slash commands: `/slop approve`, `/slop reject`, or `/slop false-positive`. Nothing is ever auto-closed.
The defining design decision is that it runs entirely on heuristics, with no LLM key required. That removes per-call API costs and avoids the latency and availability risk of routing every PR through an external model. The tradeoff is that the detection ceiling is fixed to the heuristic set — the system does not learn from your corrections in the way a model-backed classifier would, and as generation patterns evolve the recall figure the vendor reports against its 25-case golden set will need manual ruleset updates to hold.
Public repositories get the GitHub App install at no cost, according to the vendor’s site. Self-hosting is source-available under Commons Clause, which permits personal use but restricts commercial redistribution. There is no API, so any workflow that requires reading SlopGuard’s scores programmatically — to feed a dashboard, trigger a downstream automation, or integrate with a separate triage system — has no supported path. Teams that outgrow label-and-comment-only output and want to route flagged PRs into a wider workflow will be building around the tool, not with it.
Installation is one click from the GitHub App directory with no secrets, no Action YAML, and no CI configuration needed. The threshold slider is adjustable per repository, and the vendor’s live demo shows PRs reclassifying between quarantined and passed in real time as the line moves — which means you can tune aggressiveness per project without touching config files.
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