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Reads and summarizes local text-based files such as Markdown, JSON, CSV, and source code, including quick type checks and smart tailing for big logs while skipping PDFs, images, and binaries.

Scans repository context and chat history to recommend awesome-copilot Custom Agent files that are missing or outdated locally, outlines relevance/rationale, and waits for user approval before installing or updating.

This skill helps developers accurately find and explore the correct Windows API for specific platform capabilities, such as file access, camera usage, notifications, or UI controls. It searches a comprehensive local cache of WinMD metadata, providing full technical details including methods, properties, events, and enumeration values for APIs sourced from the Windows Platform SDK and WinAppSDK. It is indispensable when building complex features requiring deep integration with the Windows operating system.

This guide provides techniques for conducting effective crime investigations in non-English speaking countries (e.g., Thailand, Malaysia, Latin America). It teaches investigators to move beyond generic English searches by incorporating local language terms, specific regional place names, and local media terminology to find comprehensive and relevant information.

Evolver is a comprehensive self-evolution engine designed for autonomous AI agents. It analyzes complex runtime history, identifies performance bottlenecks, and autonomously generates and applies improvements. Communication is architecturally confined to a local Proxy Mailbox, ensuring secure and reliable interaction with the EvoMap Hub for asset management and task acquisition. Ideal for developing highly adaptive, continuously improving intelligent systems.

Plans, audits, and safely runs ChicagoHAI HypoGeniC/HypoRefine workflows for LLM-assisted hypothesis generation from labeled text datasets, with pinned installs, config validation, dataset leakage checks, and bounded local review before any model call.

Safely integrate with the official LabArchives ELN API and Inventory API v1: pick regional endpoints, build HMAC-SHA-512 signed requests, handle user authorization and UID flows, and validate local lab containers with bundled Python tools.

A comprehensive guide for optimizing query latency in Qdrant. This resource explains advanced performance tuning techniques, focusing on critical resource management like RAM utilization, segment count adjustments, and HNSW parameter tuning. It details strategies for scaling, quantization, and hardware considerations (e.g., local NVMe) to ensure consistently low-latency search performance, and outlines common pitfalls to avoid.

This skill covers using the SHAP library to explain and audit machine learning predictions. It guides users on selecting explainers, computing feature attributions, and validating results. It includes workflows for local and global visualizations, handling multi-output models, and ensuring model behavior descriptions are accurate without implying causality. Requires Python 3.12+ and specific SHAP versions.

This guide details setting up a robust, local development loop for Adobe integrations (Firefly, PDF, Photoshop). It covers using the `aio` CLI for App Builder, implementing hot reload, and establishing unit/integration testing with mocking to ensure rapid, reliable iteration cycles for Adobe APIs.

A comprehensive guide to setting up a full-cycle local Web3 development workflow. This skill utilizes Alchemy as the RPC provider, Hardhat for local unit testing, and integrates Mainnet forking and Sepolia testnet deployment. It covers initializing the project, configuring smart contract interactions, and implementing advanced testing patterns.

This guide provides a comprehensive setup for a fast and reliable local development loop for applications powered by the Anthropic Claude API. It covers environment management, implementing hot reloading, tracking API usage costs, and utilizing mock responses to ensure a smooth, rapid iteration cycle for AI developers.