Portfolio case study
AntiRot - Research Artifact Linter
Open-source CLI that catches unsupported claims, broken citations, weak source anchors, and draft markers in AI-written research drafts.
Overview
AntiRot is a local-first review harness for Markdown research artifacts. It turns the final draft into a gateable surface by flagging unsupported claims, missing source anchors, citation mismatches, comparative hype, absolute overclaim language, and leftover draft markers before a paper, proposal, or lab note ships. The current public release adds paragraph-aware parsing, in-document references support, safer citation verification, and GitHub Actions coverage for text, JSON, Markdown, and SARIF outputs.
What It Covers
- Catches unsupported claims, citation drift, hype language, comparative overreach, absolute claims, and leftover draft markers in Markdown drafts
- Supports paragraph-aware source carry, footnotes, inline links, DOIs, arXiv ids, and in-document references sections
- Runs locally with no API key and no network dependency, so it fits agent loops, proposals, and paper pipelines
- Emits text, JSON, Markdown, and SARIF outputs for terminal use, CI gates, and GitHub-native review flows
Stack And Topics
- Python
- CLI
- Markdown
- SARIF
- GitHub Actions
- Research Agents
Public Signals
- Public release: v0.2.0 GitHub release
- Output formats: 4 text, json, markdown, sarif
- Issue families: 8 unsupported, numeric, citation-not-found, citation-unverified, hype, comparative, absolute, draft markers
- Runtime deps: 0 standard-library CLI