brycewang-stanford/zotero-ai-butler-guide
skills/43-wentorai-research-plugins/skills/literature/fulltext/zotero-ai-butler-guide/SKILL.md
AI-powered paper summarization plugin for Zotero
$ install --global
skillsauthnpx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research zotero-ai-butler-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 19, 2026, 2:16 AM11.5s1 file scanned
SKILL.md
- name:
- zotero-ai-butler-guide
- description:
- AI-powered paper summarization plugin for Zotero
- 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 Guide
Overview
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).
Installation
# Download .xpi from GitHub releases
# Zotero 7: Tools → Add-ons → Install Add-on From File
Configuration
### 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
Features
Paper Summarization
### 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
Key Finding Extraction
### 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?
Paper Comparison
### 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
Q&A Mode
### 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"
Batch Processing
### 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
Custom Prompts
### 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.
Integration with Zotero Workflow
### 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
Use Cases
- Rapid screening: Quick summaries for literature triage
- Paper comprehension: Ask clarifying questions
- Comparison studies: Side-by-side paper analysis
- Data extraction: Structured information for systematic reviews
- Reading preparation: Generate briefings before journal club
References
- Zotero AI Butler GitHub
- Zotero Plugin Development
Related Skills
brycewang-stanford/thematic-analysis
development
VerifiedTrustedCommunity
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
1,685SKILL.mdUpdated Jun 5, 2026
brycewang-stanford/slr-prisma
development
VerifiedTrustedCommunity
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
1,685SKILL.mdUpdated Jun 5, 2026
brycewang-stanford/running-placebo-analysis
testing
VerifiedTrustedCommunity
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
1,685SKILL.mdUpdated Jun 5, 2026
brycewang-stanford/running-causalpy-experiments
data-ai
VerifiedTrustedCommunity
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.
1,685SKILL.mdUpdated Jun 5, 2026