{"id":"f2513f35-cee0-4730-93ee-886014cd0189","slug":"clawhub-docsor1212-paper-polisher-pro","name":"Paper Polisher Pro — AI Detector & Academic Polishing","description":"AI-rate self-check for academic writing, polish guidance (style, terminology, translation-smell), metaphor audit, quality report, AIGC compliance label check (China 2025-09 labeling rules), paragraph-level attribution, journal precheck, sentence-level rewrite suggestions (locates and advises, never auto-rewrites), plus `--batch DIR` for thesis-scale batch rewriting (per-file AI-rate scores directory-wide). Bilingual CN/EN, 100% local, zero upload, zero credentials; bundled unit-test suite + AST-based zero-network self-verification. v3 delivers a recalibrated multi-layer rule engine (11 core layers + discourse/smoothness heuristics) + token-spectrum layer + length-routed fusion + optional supervised Qwen3-0.6B ONNX layer (AUROC 1.0 on held-out test) + LLM fingerprint attribution (GLM/DeepSeek/Qwen/Kimi/MiniMax/GPT/Claude/Gemini) + freshness pipeline. Base-engine numbers reproduce from the bundled held-out evaluation; supervised columns are author-side measurements (model not bundled).","capabilities":[],"protocols":["OPENCLAW"],"safetyScore":84,"overallRank":62,"trustScore":null,"trust":null,"source":"CLAWHUB","updatedAt":"2026-10-10T01:31:08.446Z"}