Skill UI

Fetch Hugging Face paper pages or arXiv entries with markdown and API calls to pull abstracts, metadata, authorship, upvotes, and linked models/datasets/spaces so you can summarize or analyze AI research efficiently.

Trackio is a robust library designed for comprehensive monitoring and management of Machine Learning experiments. It allows users to log key training metrics, set structured alerts (e.g., loss divergence, NaN gradients), and visualize results over time. The system supports integration via Python API for logging/alerting, and a powerful CLI for programmatic metric retrieval and dashboard synchronization to Hugging Face Spaces. Ideal for autonomous AI agent workflows and detailed research tracking.

Fine-tune or train object detection, classification, and SAM/SAM2 segmentation models on Hugging Face Jobs, leveraging managed GPUs, automatic dataset checks, and Hub persistence without local GPU setup.

Implements comprehensive external attack surface management using Shodan, Censys, subfinder, httpx, and nuclei to discover assets, enumerate services, and score exposures for continuous ASM or pentest reconnaissance.

Sets up Microsoft Purview data loss prevention policies to protect sensitive content across Exchange, SharePoint, OneDrive, Teams, Power BI, and managed endpoints by defining sensitivity label taxonomies, custom regex types, endpoint controls, and monitoring with Activity Explorer plus PowerShell/Graph automation.

Provides direct REST access to UniProt for searching proteins, retrieving sequences/annotations, mapping IDs, and streaming large datasets in workflows that demand precise protein data.

Guides you through planning video content strategy, scripting long-form and short-form assets, building YouTube pipelines, and repurposing existing material into high-impact videos for discovery, trust, and conversions.

Manage Google Drive assets end-to-end—locate Docs, Sheets, or Slides, inspect their structure, perform precise edits, and keep shared workflows clean without resorting to raw tool calls.

Automates preparing private repos for safe public release through a three-stage pipeline that forks the project, scans and sanitizes secrets, and generates CLAUDE.md, setup scripts, and documentation for GitHub publication.

Workspace Surface Audit scans repo files, MCP servers, plugins, connectors, and environment configs to report current capabilities and recommend ECC-native skills, hooks, agents, or workflows for setups like Claude Code.

A comprehensive solution for systematically auditing dataset health. It profiles data distributions, detects missing values (MCAR/MAR/MNAR), identifies outliers using multiple methods (IQR, Z-score), and calculates a Data Quality Score (DQS). It provides actionable remediation plans and supports monitoring setup for live pipelines.

Automates updating the Context Mode plugin: fetches the latest GitHub version, rebuilds and installs it, updates the global npm config, and ensures hooks are set, reporting progress through a checklist; falls back to a CLI upgrade command if ctx_upgrade MCP fails.