Skill UI

A comprehensive tool for updating Feishu cloud documents. It supports seven distinct update modes including appending, full overwrite, targeted range replacement, and multi-instance replacement. The system allows highly precise positioning using content ranges (ellipsis) or chapter titles, ensuring content updates are localized and safe, thus preserving images, comments, and formatting.

This guide details the process of deploying production-grade inference services on CoreWeave using KServe. It covers setting up autoscaling, GPU scheduling, and implementing scale-to-zero functionality for efficient ML model serving endpoints. Ideal for MLOps engineers deploying large language models (LLMs) or other complex AI models in a production environment.

This reference architecture provides a comprehensive blueprint for deploying Machine Learning models on CoreWeave's GPU cloud infrastructure. It details the structure for multi-model serving (e.g., vLLM, TGI), scalable Kubernetes deployments, shared persistent storage (PVC), and autoscaling mechanisms using KServe/Knative. Use this when designing robust MLOps pipelines, planning high-performance multi-model inference services, or establishing standardized best practices for GPU cloud deployment.

This skill provides real-time monocular depth estimation using advanced models like Depth Anything v2. It transforms live camera feeds by generating colorized depth maps, enabling depth overlays and detailed scene understanding. Crucially, it supports a 'privacy mode' that anonymizes visual identities by using depth-only transformation, preserving only the spatial layout and movement patterns for secure monitoring purposes. Optimized for both CoreML on macOS and PyTorch on other platforms.

This skill governs the secure ingestion and indexing of enterprise documents from diverse connectors (e.g., Google Drive, Confluence, Jira). Key functions include mandatory PII filtering (stripping emails, phones, SSNs) before indexing, preserving strict permission boundaries, and enforcing data retention policies to ensure compliance with global regulations like GDPR and CCPA.

A comprehensive guide detailing five validated architecture patterns for utilizing Notion as a powerful backend database. Use cases include: Headless CMS for blogging, task tracking for project management, building knowledge bases (wikis), handling form submissions, and serving as a data pipeline source. Includes schema design and code examples using TypeScript and Python.

This skill guides developers through creating a comprehensive refactoring plan and serving as a Request for Comments (RFC). It orchestrates detailed interviews, codebase analysis, and scope definition. It ensures the refactor is broken down into tiny, safe, incremental commits, culminating in a structured GitHub issue that serves as a definitive architectural and technical decision document.

A comprehensive guide detailing professional data migration strategies for Salesforce. It covers utilizing Bulk API 2.0, implementing ETL patterns, complex schema mapping, and preserving object relationships (parent-child). Ideal for large-scale CRM data transfers, org-to-org migrations, and data re-platforming.

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.

This CLI alias functions as a command for gracefully canceling an active PUA loop, mirroring the functionality of the Claude Code `/pua:cancel-loop` command. It cleans up loop state and worktree references, ensuring the cancellation event is recorded. It also safely manages configuration files, preserving unknown fields in `~/.pua/config.json`.

This utility serves as a Command Line Interface (CLI) alias for managing 'flavor' profiles within AI code environments (like Claude Code). It allows users to set or select specific configuration flavors in the ~/.pua/config.json file. Crucially, it is designed to safely update the configuration by preserving any unknown fields, ensuring no unrelated settings are accidentally overwritten.

This utility serves as a command-line alias for invoking the Claude Code `/pua:kpi` function. It loads necessary configurations (pua-pro) to generate comprehensive Key Performance Indicator (KPI) or performance report cards. It manages configuration files by updating `~/.pua/config.json` while preserving unknown fields and ensuring the directory structure exists.