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Initialize HuggingFace integration - validates .env variables, tests API connectivity, and ensures the dataset repository structure exists. Use when onboarding a new project to HuggingFace or when credentials change.
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Guides the creation of agile user stories and Gherkin feature files. Use when the user wants to create a user story, write acceptance criteria, define Gherkin scenarios, or author BDD feature files. This should trigger for requests such as Create a user story; Write a user story; I need to write a user story. Part of cursor-rules-java project
Guía técnica completa para integrar 250+ servicios externos con agentes IA usando Composio. Cubre instalación, autenticación OAuth, gestión de herramientas, triggers y flujos multi-servicio.
Facilitates conversational discovery to create Architectural Decision Records (ADRs) for non-functional requirements using the ISO/IEC 25010:2023 quality model. Use when the user wants to document quality attributes, NFR decisions, security/performance/scalability architecture, or design systems with measurable quality criteria. This should trigger for requests such as Create ADR for Non-functional requirements; Document Non-functional requirements; Capture Non-functional requirements; Generate Non-functional requirements in an ADR. Part of cursor-rules-java project
基于 SOC 职业分类
正在显示 SKILL.md
| name | hf-init |
| description | Initialize HuggingFace integration - validates .env variables, tests API connectivity, and ensures the dataset repository structure exists. Use when onboarding a new project to HuggingFace or when credentials change. |
| allowed-tools | Bash, Read |
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).
Status: Active Author: Richard Fremmerlid Domain: HuggingFace Integration
Sets up everything needed for HuggingFace persistence. Run this once when onboarding a new project, or whenever credentials change.
.env variables are setlineage/, data/, metadata/)| 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) |
python ./hf_config.py
python ./hf_init.py
python ./hf_init.py --validate-only
# 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