brycewang-stanford
brycewang-stanford/Auto-Empirical-Research-Skills
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/brycewang-stanford/Auto-Empirical-Research-Skills --skill zotero-ai-butler-guide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。
正在显示 SKILL.md
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.
基于 SOC 职业分类
| name | zotero-ai-butler-guide |
| description | AI-powered paper summarization plugin for Zotero |
| metadata | {"openclaw":{"emoji":"🤵","category":"literature","subcategory":"fulltext","keywords":["Zotero","AI summary","paper summarization","LLM","abstract generation","reading assistant"],"source":"https://github.com/steven-jianhao-li/zotero-AI-Butler"}} |
Zotero AI Butler is a Zotero plugin that uses LLMs to summarize, analyze, and annotate academic papers directly within Zotero. It can generate structured summaries, extract key findings, compare papers, and answer questions about documents — all without leaving the reference manager. Supports multiple LLM backends (OpenAI, Claude, local models).
# Download .xpi from GitHub releases
# Zotero 7: Tools → Add-ons → Install Add-on From File
### LLM Backend Setup (Preferences → AI Butler)
**Option 1: OpenAI**
- Provider: OpenAI
- Model: gpt-4o
- Set environment variable for credentials
**Option 2: Anthropic**
- Provider: Anthropic
- Model: claude-sonnet-4-20250514
**Option 3: Local (Ollama)**
- Provider: Ollama
- Endpoint: http://localhost:11434
- Model: llama3.1
**Option 4: Custom API**
- Provider: Custom
- Endpoint: your-api-url
- Compatible with OpenAI API format
### Usage
1. Select paper in Zotero
2. Right-click → AI Butler → Summarize
3. Summary added as Zotero note
### Summary Templates
- **Quick Summary** (1 paragraph): Core contribution + method + result
- **Structured Summary**: Background / Method / Results / Limitations
- **Executive Brief**: Who should read this and why
- **Technical Deep-Dive**: Detailed methodology and math
### Extract structured information:
- **Research question**: What problem does this paper address?
- **Methodology**: What approach do the authors use?
- **Key results**: What are the main findings?
- **Contributions**: What is novel about this work?
- **Limitations**: What are the acknowledged limitations?
- **Future work**: What directions do the authors suggest?
### Compare multiple papers:
1. Select 2+ papers in Zotero
2. Right-click → AI Butler → Compare Papers
3. Generates comparison table:
- Shared and unique contributions
- Methodological differences
- Performance comparison (if applicable)
- Complementary insights
### Ask questions about papers:
1. Open paper in Zotero reader
2. AI Butler sidebar → Ask a question
3. Answers grounded in paper content with page references
Example questions:
- "What loss function do they use?"
- "How does this compare to prior work?"
- "What are the hyperparameters?"
- "Explain equation 3 in simpler terms"
### Summarize multiple papers:
1. Select papers (or entire collection)
2. Right-click → AI Butler → Batch Summarize
3. Progress bar shows completion
4. Each paper gets a summary note attached
### Reading List Generation:
1. Select collection
2. AI Butler → Generate Reading Order
3. Suggests optimal reading sequence based on:
- Citation relationships
- Conceptual dependencies
- Publication chronology
### Create custom analysis prompts:
# In AI Butler preferences → Custom Prompts
Prompt: "Systematic Review Extraction"
Template: |
Extract the following from this paper:
1. Study design (RCT, cohort, etc.)
2. Sample size
3. Primary outcome
4. Effect size with CI
5. Risk of bias indicators
Format as structured JSON.
### Combined Plugin Workflow
1. **Zotero Connector** → Import paper
2. **Zotero Sci-Hub** → Fetch PDF
3. **AI Butler** → Generate summary note
4. **Zotero Actions Tags** → Auto-tag based on summary
5. **Notero** → Sync to Notion with summary
6. **Better BibTeX** → Export citations for writing