7-e1even
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learn-agent
A collection of notes on building coding agents, derived from the production development of the desktop agent Reina, with each mechanism simplified into a zero-dependency, single-file Node.js demo.
Zotero_Paper_Classification_XT
XT Zotero Paper Auto Classifier is a Zotero plugin that uses a large language model API to automatically classify papers into dynamic, medium-grained topic collections based on title, abstract, and keywords.
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MIT
Last updated
2026-07-30
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FR-AI / ANALYSISWhy it is worth attention
It leverages LLM to dynamically create topic collections tailored to the user's library without requiring a fixed taxonomy or external tools, and includes both full and supplemental classification modes with cleanup support.
Who it is for
- Zotero users managing large literature collections
- Researchers and academics who want automated paper organization
- Students organizing references for thesis or projects
- Anyone who prefers a configurable, LLM-driven classification system
Use cases
- Automatically classify newly added papers into relevant topic collections
- Rebuild the entire classification tree after changing category language or model
- Supplement classification for unmarked papers without disrupting existing folders
- Clean up all XT-generated collections and tags while preserving paper records
Strengths
- Uses LLM to generate categories dynamically based on actual paper content
- Supports multiple classification modes (full and supplemental) for flexible workflows
- Reuses existing collections when appropriate, reducing redundant categories
- No external dependencies like Python, Anaconda, or Zotero Web API key required
Considerations
- Requires a valid API key from a supported LLM provider and network access
- Initial classification time depends on library size, abstract length, and model speed
- Classification results are model-generated and may need manual review for accuracy
README quick start
Installation
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