tools/doc/SKILL.md
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.
npx skillsauth add letta-ai/skills docInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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soffice and pdftoppm are available, convert DOCX -> PDF -> PNGs.scripts/render_docx.py (requires pdf2image and Poppler).python-docx for edits and structured creation (headings, styles, tables, lists).python-docx as a fallback and call out layout risk.tmp/docs/ for intermediate files; delete when done.output/doc/ when working in this repo.Prefer uv for dependency management.
Python packages:
uv pip install python-docx pdf2image
If uv is unavailable:
python3 -m pip install python-docx pdf2image
System tools (for rendering):
# macOS (Homebrew)
brew install libreoffice poppler
# Ubuntu/Debian
sudo apt-get install -y libreoffice poppler-utils
If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally.
No required environment variables.
DOCX -> PDF:
soffice -env:UserInstallation=file:///tmp/lo_profile_$$ --headless --convert-to pdf --outdir $OUTDIR $INPUT_DOCX
PDF -> PNGs:
pdftoppm -png $OUTDIR/$BASENAME.pdf $OUTDIR/$BASENAME
Bundled helper:
python3 scripts/render_docx.py /path/to/file.docx --output_dir /tmp/docx_pages
testing
Navigates archived ChatGPT or Claude-style conversation exports and a MemFS reference archive on demand. Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.
testing
Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.
data-ai
Configures Letta agent compaction settings and custom summarization prompts. Use when a user asks to change an agent's compaction prompt, improve summaries after context eviction, tune sliding-window or all-message compaction, or design companion/coding-agent continuity summaries.
development
Semantic search over agent memory files. Use when you need to find conceptually related memory blocks, discover forgotten reference files, check what you already know before creating new memory, or search beyond exact keyword matching. Currently supports QMD (local, no API keys).