hf-init
Dependencies
This skill requires Python 3.8+ and standard library only. No external packages needed.
To install this skill's dependencies:
pip-compile ./requirements.in
pip install -r ./requirements.txt
See ./requirements.txt for the dependency lockfile (currently empty — standard library only).
HuggingFace Init (Onboarding)
Status: Active Author: Richard Fremmerlid Domain: HuggingFace Integration
Purpose
Sets up everything needed for HuggingFace persistence. Run this once when onboarding a new project, or whenever credentials change.
What It Does
- Validates required
.envvariables are set - Tests API connectivity with the configured token
- Ensures the dataset repository exists on HF Hub
- Creates the standard folder structure (
lineage/,data/,metadata/) - Uploads the dataset card (README.md) with configurable discovery tags
Required Environment Variables
| Variable | Required | Description |
|---|---|---|
HUGGING_FACE_USERNAME |
✅ Yes | Your HF username |
HUGGING_FACE_TOKEN |
✅ Yes | API token (set in ~/.zshrc, NOT .env) |
HUGGING_FACE_REPO |
✅ Yes | Model repo name |
HUGGING_FACE_DATASET_PATH |
✅ Yes | Dataset repo name |
HUGGING_FACE_TAGS |
❌ No | Comma-separated discovery tags for dataset card |
HUGGING_FACE_PROJECT_NAME |
❌ No | Pretty name for dataset card heading |
SOUL_VALENCE_THRESHOLD |
❌ No | Moral/emotional charge filter (default: -0.7) |
Usage
Validate Config
python ./hf_config.py
Full Init (Validate + Create Structure + Dataset Card)
python ./hf_init.py
Validate Only (No Changes)
python ./hf_init.py --validate-only
Quick Setup
# Token goes in shell profile (never committed):
export HUGGING_FACE_TOKEN=hf_xxxxxxxxxxxxx
# Project vars go in .env:
HUGGING_FACE_USERNAME=<your-username>
HUGGING_FACE_REPO=<your-model-repo>
HUGGING_FACE_DATASET_PATH=<your-dataset-repo>
# Optional customization:
HUGGING_FACE_TAGS=reasoning-traces,cognitive-continuity,your-project-tag
HUGGING_FACE_PROJECT_NAME=My Project Soul
# Run init
python ./hf_init.py
More from richfrem/agent-plugins-skills
markdown-to-msword-converter
Converts Markdown files to one MS Word document per file using plugin-local scripts. V2 includes L5 Delegated Constraint Verification for strict binary artifact linting.
52excel-to-csv
>
32zip-bundling
Create technical ZIP bundles of code, design, and documentation for external review or context sharing. Use when you need to package multiple project files into a portable `.zip` archive instead of a single Markdown file.
29learning-loop
(Industry standard: Loop Agent / Single Agent) Primary Use Case: Self-contained research, content generation, and exploration where no inner delegation is required. Self-directed research and knowledge capture loop. Use when: starting a session (Orientation), performing research (Synthesis), or closing a session (Seal, Persist, Retrospective). Ensures knowledge survives across isolated agent sessions.
26ollama-launch
Start and verify the local Ollama LLM server. Use when Ollama is needed for RLM distillation, seal snapshots, embeddings, or any local LLM inference — and it's not already running. Checks if Ollama is running, starts it if not, and verifies the health endpoint.
26spec-kitty-checklist
A standard Spec-Kitty workflow routine.
26