sci-download
学术论文 PDF 下载。支持 8 个数据源:Elsevier、Springer Nature、IEEE Xplore、 arXiv、Unpaywall、Semantic Scholar、PubMed Central、知网(CNKI)。 自动根据 DOI 前缀路由到对应数据源,未知 DOI 自动尝试 Unpaywall…
Two-stage academic paper polishing skill. Stage A reduces AI detection traces (targeting GPTZero, Turnitin, Originality.ai). Stage B performs 8-dimension quality improvement (grammar, tone, coherence, conciseness, terminology, structure, argument clarity, journal compliance).
$ npx -y skills add ShZhao27208/Aut_Sci_Write --skill sci-polish --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/sci-polishContext preview
The summary Claude sees to decide when to auto-load this skill.
Two-stage academic paper polishing skill. Stage A reduces AI detection traces (targeting GPTZero, Turnitin, Originality.ai). Stage B performs 8-dimension quality improvement (grammar, tone, coherence, conciseness, terminology, structure, argument clarity, journal compliance).
name: sci-polish description: > Two-stage academic paper polishing skill. Stage A reduces AI detection traces (targeting GPTZero, Turnitin, Originality.ai). Stage B performs 8-dimension quality improvement (grammar, tone, coherence, conciseness, terminology, structure, argument clarity, journal compliance). Use whenever the user asks to polish, proofread, humanize, reduce AI rate, improve writing quality, or prepare a paper for submission. author: Shuo Zhao license: MIT copyright: © 2026 Shuo Zhao. All rights reserved. triggers: - 润色论文 - polish paper - reduce AI detection - 降AI率 - de-AI - humanize paper - academic polish - 论文润色 - 学术改写 - improve writing - proofread - 降低AI率 - 论文降重 - paper polishing - rewrite academic
Two-stage academic paper polishing: AI trace reduction + 8-dimension quality improvement.
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1. **NEVER modify:** LaTeX commands, math environments (`$...$`, `\[...\]`, `equation`, `align`, etc.), `\cite{}`, `\ref{}`, `\label{}`, algorithm blocks, code listings, figure/table environments (only caption text is editable) 2. **NEVER fabricate:** data, citations, experimental results, baselines, metrics, author names 3. **NEVER remove:** author's technical claims without explicit permission 4. **NEVER introduce:** Tier 1 AI words (see `references/word-choice-anti-ai.md`) during Phase B edits 5. **Mark as `[PENDING VERIFICATION]`:** any claim you cannot verify from the text 6. **Preserve meaning:** the exact semantic content of every technical statement must be unchanged 7. **Output format:** revised text + polish report. No preamble or trailing changelog unless user asks 8. **When uncertain about domain terminology:** keep the original, flag for user review
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| Mode | Command | Behavior | |------|---------|----------| | `full` (default) | "polish this paper" | Phase A → Phase B (all 8 dimensions) | | `deai-only` | "just reduce AI rate" / "只降AI率" | Phase A only | | `polish-only` | "just polish, skip de-AI" / "只润色" | Phase B only (all 8 dimensions) | | `polish-select` | "fix grammar and coherence" | Phase B, selected dimensions only |
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1. **Identify input format:**
2. **Identify protection zones:** math environments, citations, labels, algorithm blocks, code blocks, figure/table environments 3. **Ask target journal** (optional): affects Dimension 8 scoring. If not specified, use general academic standards. 4. **Confirm execution mode:** full / deai-only / polish-only / polish-select
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Reference files:
Scan text against `ai-detection-patterns.md`. Categorize findings:
Follow the strategy priority from `de-ai-strategies.md`:
a. Burstiness enforcement — restructure sentence lengths (Strategy 1) Target: SD > 8, range ≥ 20, mid-band < 50% b. Vocabulary de-AI — replace Tier 1 words, compress template phrases (Strategy 2) Consult word-choice-anti-ai.md for replacements c. Sentence restructuring — vary syntax patterns (Strategy 3) No 3+ consecutive same-structure sentences d. Concept concretization — add specifics where available (Strategy 4) Replace vague claims with data from the paper itself e. Argumentation enrichment — add depth to claims (Strategy 5) Insert boundary conditions, alternative interpretations f. Perplexity elevation — introduce unpredictability (Strategy 6) Unconventional openers, domain-specific minor terms g. Style disruption — break uniformity (Strategy 7) Vary paragraph density and register between sections
After rewriting, re-scan output against `ai-detection-patterns.md`:
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Reference file: `references/polish-dimensions.md`
Rate each dimension based on the checkpoints in `polish-dimensions.md`: 1. Grammar & Syntax 2. Academic Tone 3. Coherence & Flow 4. Conciseness 5. Terminology 6. Structure & Formatting 7. Clarity of Argument 8. Journal Compliance
Edit in this order (foundation → logic → style → format):
Dim 1 (Grammar) → Dim 7 (Clarity) → Dim 3 (Coherence) → Dim 4 (Conciseness) → Dim 2 (Tone) → Dim 5 (Terminology) → Dim 6 (Structure) → Dim 8 (Journal)
During Phase B editing, verify Phase A improvements are maintained:
Rate edited dimensions again. Record "Before" and "After" scores for the report.
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Output the complete polished text with all modifications applied. Format matches the input format (LaTeX → LaTeX, Markdown → Markdown, etc.).
Generate report using `templates/polish-report.md`:
Autonomous Scientific Writer A modular Agent Skills suite for the full academic research lifecycle
Repo: ShZhao27208/Aut_Sci_Write
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