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Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill research-lit명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | research-lit |
| description | Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers. |
Research topic: $ARGUMENTS
papers/ in the current project directoryliterature/ in the current project directoryAGENTS.md under ## Paper Librarytrue, download top 3-5 most relevant arXiv PDFs to PAPER_LIBRARY after search. When false (default), only fetch metadata (title, abstract, authors) via arXiv API — no files are downloaded.ARXIV_DOWNLOAD = true.💡 Overrides:
/research-lit "topic" — paper library: ~/my_papers/— custom local PDF path/research-lit "topic" — sources: zotero, local— only search Zotero + local PDFs/research-lit "topic" — sources: zotero— only search Zotero/research-lit "topic" — sources: web— only search the web (skip all local)/research-lit "topic" — arxiv download: true— download top relevant arXiv PDFs
/research-lit "topic" — arxiv download: true, max download: 10 — download up to 10 PDFsThis skill checks multiple sources in priority order. All are optional — if a source is not configured or not requested, skip it silently.
Parse $ARGUMENTS for a — sources: directive:
— sources: is specified: Only search the listed sources (comma-separated). Valid values: zotero, obsidian, local, web, all.all — search every available source in priority order.Examples:
/research-lit "diffusion models" → all (default)
/research-lit "diffusion models" — sources: all → all
/research-lit "diffusion models" — sources: zotero → Zotero only
/research-lit "diffusion models" — sources: zotero, web → Zotero + web
/research-lit "diffusion models" — sources: local → local PDFs only
/research-lit "topic" — sources: obsidian, local, web → skip Zotero
| Priority | Source | ID | How to detect | What it provides |
|---|---|---|---|---|
| 1 | Zotero (via MCP) | zotero | Try calling any mcp__zotero__* tool — if unavailable, skip | Collections, tags, annotations, PDF highlights, BibTeX, semantic search |
| 2 | Obsidian (via MCP) | obsidian | Try calling any mcp__obsidian-vault__* tool — if unavailable, skip | Research notes, paper summaries, tagged references, wikilinks |
| 3 | Local PDFs | local | Glob: papers/**/*.pdf, literature/**/*.pdf | Raw PDF content (first 3 pages) |
| 4 | Web search | web | Always available (WebSearch) | arXiv, Semantic Scholar, Google Scholar |
Graceful degradation: If no MCP servers are configured, the skill works exactly as before (local PDFs + web search). Zotero and Obsidian are pure additions.
Skip this step entirely if Zotero MCP is not configured.
Try calling a Zotero MCP tool (e.g., search). If it succeeds:
/paper-write later)📚 Zotero annotations are gold — they show what the user personally highlighted as important, which is far more valuable than generic summaries.
Skip this step entirely if Obsidian MCP is not configured.
Try calling an Obsidian MCP tool (e.g., search). If it succeeds:
#diffusion-models, #paper-review)📝 Obsidian notes represent the user's processed understanding — more valuable than raw paper content for understanding their perspective.
Before searching online, check if the user already has relevant papers locally:
Locate library: Check PAPER_LIBRARY paths for PDF files
Glob: papers/**/*.pdf, literature/**/*.pdf
De-duplicate against Zotero: If Step 0a found papers, skip any local PDFs already covered by Zotero results (match by filename or title).
Filter by relevance: Match filenames and first-page content against the research topic. Skip clearly unrelated papers.
Summarize relevant papers: For each relevant local PDF (up to MAX_LOCAL_PAPERS):
Build local knowledge base: Compile summaries into a "papers you already have" section. This becomes the starting point — external search fills the gaps.
📚 If no local papers are found, skip to Step 1. If the user has a comprehensive local collection, the external search can be more targeted (focus on what's missing).
arXiv API search (always runs, no download by default):
Locate the fetch script and search arXiv directly:
# Try to find arxiv_fetch.py
SCRIPT=$(find tools/ -name "arxiv_fetch.py" 2>/dev/null | head -1)
# If not found, check ARIS install
[ -z "$SCRIPT" ] && SCRIPT=$(find ~/.codex/skills/arxiv/ -name "arxiv_fetch.py" 2>/dev/null | head -1)
# Search arXiv API for structured results (title, abstract, authors, categories)
python3 "$SCRIPT" search "QUERY" --max 10
If arxiv_fetch.py is not found, fall back to WebSearch for arXiv (same as before).
The arXiv API returns structured metadata (title, abstract, full author list, categories, dates) — richer than WebSearch snippets. Merge these results with WebSearch findings and de-duplicate.
Optional PDF download (only when ARXIV_DOWNLOAD = true):
After all sources are searched and papers are ranked by relevance:
# Download top N most relevant arXiv papers
python3 "$SCRIPT" download ARXIV_ID --dir papers/
For each relevant paper (from all sources), extract:
Present as a structured literature table:
| Paper | Venue | Method | Key Result | Relevance to Us | Source |
|-------|-------|--------|------------|-----------------|--------|
Plus a narrative summary of the landscape (3-5 paragraphs).
If Zotero BibTeX was exported, include a references.bib snippet for direct use in paper writing.
literature/ or papers/mcp__zotero__search or mcp__zotero-mcp__search_items). Try the most common patterns and adapt.