用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/KYRIE66nb/codex-omx-public-config --skill research-lit命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | research-lit |
| description | Search and analyze 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 PDFs
This 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.