Stats
Actions
Tags
From easypaper
Automatically set up EasyPaper environment including Python dependencies and LaTeX toolchain in an isolated environment.
How this skill is triggered — by the user, by Claude, or both
Slash command
/easypaper:easypaper-setup-environmentThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use this skill when the plugin is first installed or when environment setup is needed.
Use this skill when the plugin is first installed or when environment setup is needed.
uv is available (preferred) or python/python3uv is available, use it to create an isolated virtual environmentvenv or virtualenv and create a virtual environment.venv or .easypaper-env)uv is available:
uv venv .easypaper-env
source .easypaper-env/bin/activate # or .easypaper-env/Scripts/activate on Windows
uv pip install -e . # if in repo root
# OR
uv pip install easypaper[server] # if installing from PyPI
python -m venv .easypaper-env
source .easypaper-env/bin/activate
pip install -e . # or pip install easypaper[server]
pdflatex command, suggest brew install --cask mactex or brew install basictexpdflatex, suggest sudo apt-get install texlive-full or texlive-basepdflatex, suggest installing MiKTeX or TeX Livepdflatex --versionpython -c "import easypaper; from easypaper import EasyPaper, PaperMetaData; print('EasyPaper imported successfully')"pdflatex --versionCreate a helper script (.easypaper-activate.sh or .easypaper-activate.bat) that:
After successful setup, inform the user:
.easypaper-envsource .easypaper-env/bin/activate (or equivalent for Windows)from easypaper import EasyPaper, PaperMetaDataconfigs/example.yaml for referencenpx claudepluginhub pinkgranite/easypaper --plugin easypaperSearches MemPalace before answering questions about past work, people, projects, or prior decisions. Returns verbatim stored content instead of guessing from model memory.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Implements vector databases with Pinecone, Weaviate, Qdrant, Milvus, pgvector for semantic search, RAG, recommendations, and similarity systems. Optimizes embeddings, indexing, and hybrid search.