huggingface
Hugging Face Skill
Purpose
Provides structured workflows for interacting with the Hugging Face ecosystem: Hub repository search, model loading and inference, dataset management, PEFT/LoRA fine-tuning, and Spaces deployment. Integrates via MCP tools when available and falls back to Python APIs and the huggingface_hub CLI.
When to Invoke
Skill({ skill: 'huggingface' });
Invoke when:
- Searching for models, datasets, or Spaces on the Hub
- Loading and running inference with Transformers models
- Managing datasets with the
datasetslibrary - Fine-tuning models with PEFT/LoRA
- Deploying or querying Hugging Face Spaces
More from oimiragieo/agent-studio
gcloud-cli
Google Cloud CLI operations and resource management
965pyqt6-ui-development-rules
PyQt6 desktop GUI development rules -- signal/slot architecture, QSS theming, QThread concurrency, layout management, and cross-platform rendering. Enforces MVC separation and responsive UI patterns.
570filesystem
File system operations guidance - read, write, search, and manage files using Claude Code's built-in tools.
360chrome-browser
Browser automation with two integrations - Chrome DevTools MCP (always available, performance tracing) and Claude-in-Chrome extension (authenticated sessions, GIF recording). Use DevTools for testing/debugging, Claude-in-Chrome for authenticated workflows.
303slack-notifications
Slack messaging, channels, and notifications - send messages, manage channels, interact with users, upload files, and add reactions. Use for team communication, incident notifications, and workflow alerts.
244context-compressor
Compress large context before reasoning to reduce token usage while preserving evidence. Use this whenever the user mentions huge files, long prompts, RAG payloads, prompt caching, expensive sessions, codebase context, chat history compaction, or wants the same answer quality with fewer tokens.
146