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让每一次引用都成为可解释的影响力
Turning Every Citation into Explainable Impact
Turn Every Citation into Explainable Impact.
Input paper titles (or import from Google Scholar profiles), and generate a full citation portrait report in minutes.
CitationClaw is community-driven and PR-friendly.
- Open an issue: https://github.com/VisionXLab/CitationClaw/issues
- Submit a PR: https://github.com/VisionXLab/CitationClaw/pulls
- Good first tasks: docs, UI polish, skill metadata, retry robustness
- 2026-03-15: Released beta v1.0.6 — English README as default, Chinese switch at top, and usage flow linked to Guidelines Quick Start.
- 2026-03-14: Released v1.0.5 — AI assistant widgets for UI/report pages and reliability fixes.
- 2026-03-14: Released v1.0.4 — improved UI and introduced Basic/Advanced/Full service tiers.
- 2026-03-12: Released v1.0 — first public release.
- 🧠 Five-Phase Citation Pipeline: crawl -> author intelligence -> export -> citing description -> dashboard.
- 🎯 Renowned Scholar Focus: auto-identifies high-impact scholars and generates dedicated outputs.
- ⚡ Tiered Analysis Modes: Basic / Advanced / Full for speed-cost-depth tradeoff.
- 🔁 Resumable + Cache-Aware: supports resume-by-page, author cache, and citing-description cache.
- 📊 Shareable HTML Report: standalone dashboard file, no extra server needed for viewing.
- 🧩 Skills Runtime Inside: keeps five-phase logic while moving execution to modular skills.
CitationClaw keeps deterministic business phases while using a skills-style runtime for orchestration.
UI/REST/WebSocket
│
▼
TaskExecutor (Orchestrator)
│
▼
Skills Runtime
├─ phase1_citation_fetch
├─ phase2_author_intel
├─ phase3_export
├─ phase4_citation_desc
└─ phase5_report_generate
More details: Technical Report
- News
- Key Features
- Architecture
- Install
- Quick Start
- Configuration Highlights
- Project Structure
- Outputs
- Contribute & Roadmap
- Community
- Star History
- Disclaimer
Requires Python 3.10+ (Python 3.12 recommended).
pip install citationclaw
citationclaw # default: 127.0.0.1:8000
citationclaw --port 8080 # custom portgit clone https://github.com/VisionXLab/CitationClaw.git
cd CitationClaw
pip install -r requirements.txt
python start.py # default: 127.0.0.1:8000
python start.py --port 8080For first-time users, follow the complete guide with screenshots:
- Required keys:
ScraperAPI Key(s)for Google Scholar crawlingOpenAI-compatible API Keyfor LLM-based analysis
- Recommended search model:
- Keep
gemini-3-flash-preview-searchfor search-capable stages
- Keep
- Service tiers:
Basic: lower cost and faster for first runsAdvanced: citing descriptions for renowned-scholar papers onlyFull: citing descriptions for all citing papers
- For papers with >1000 citations:
- Enable year traverse mode
citationclaw/
├── app/ # FastAPI app, task orchestration, config, logs
├── core/ # scraping / search / export / dashboard engines
├── skills/ # skills runtime and five phase skills
├── static/ # frontend assets
├── templates/ # Jinja2 pages
docs/ # docs and demos
test/ # tests
Each run creates a timestamped folder under data/result-{timestamp}/, usually including:
paper_results.xlsxpaper_results_all_renowned_scholar.xlsxpaper_results_top-tier_scholar.xlsxpaper_results_with_citing_desc.xlsxpaper_results.jsonpaper_dashboard.html
PRs are welcome and appreciated.
Suggested directions:
- richer skill metadata and registry conventions
- stronger retry and network-failure resilience
- dashboard readability and UX improvement
- tests for pipeline contracts and compatibility
- provider/model compatibility presets
Useful links:
- Issues: https://github.com/VisionXLab/CitationClaw/issues
- Pull Requests: https://github.com/VisionXLab/CitationClaw/pulls
- Guidelines: https://visionxlab.github.io/CitationClaw/guidelines.html
- Product update: 减论 reduct.cn
- User group (CN):
