GitHub Copilot AI Skills
Extend GitHub Copilot with verified AI skills
GitHub Copilot is the world's most widely adopted AI coding assistant, used by millions of developers. AgentPowers skills add specialized capabilities beyond code completion - framework expertise, testing automation, deployment workflows, and more - directly in VS Code, JetBrains, and other supported editors.
Top GitHub Copilot Skills
Hikvision NVR
Ask your AI agent for the Hikvision footage you need, then walk away while it downloads. Pulling video off a Hikvision DVR or NVR usually means web-UI menus, ISAPI XML, ffmpeg flags, and "why is this video broken" troubleshooting. This skill removes all of it. Once your NVRs are registered, you just tell your agent "pull the lobby camera from 8 to 9 PM yesterday" and a clean MP4 lands in your downloads folder. Speaks Hikvision's ISAPI natively, falls back to RTSP when the NVR throttles, works around firmware quirks that return wrong segment data, clips to the exact time window you asked for, and verifies the output (codec, resolution, duration, on-screen timestamp). Credentials live in your OS keychain, never on command lines or in logs. Validated on DS-9016HWI-ST, DS-7316HQHI-SH, DS-7716NI-I4/16P, DS-9632NI-ST, and DS-7716NI-SP/16 with firmware V3.1.10 through V4.50.000.
agentpass-local
Install or build a global per-user AgentPass Local that improves human-agent collaboration by letting users create website credentials in a GUI and letting agents retrieve or paste approved fields for approved domains without viewing secrets. Use when the user asks to create a password manager, password broker, credential vault, autofill helper, agent password access system, GUI for saving website credentials, or a tool that lets agents use approved passwords across projects safely.
mesh flow
What it does Mesh Flow replaces fragile, implicit prompt-chaining with a robust, artifact-driven DAG (Directed Acyclic Graph) orchestration system. By defining your agent workflows in a structured project.yaml, you move logic out of the prompt and into a compile-time validated system. It enforces hard gates—such as human approval or dependency verification—that the AI cannot bypass or hallucinate past. Why use this skill Standard agentic workflows often fail because the LLM decides to skip steps or "forgets" requirements. Mesh Flow treats your agentic workflow like a CI/CD pipeline. It features a Compile-then-Run architecture that validates your topology for cycles and missing artifacts before single token is generated. This ensures 100% predictable execution paths, explicit failure states (failed, blocked, rejected), and absolute control over recovery paths. Supported tools YAML-based workflow configurations Standardized Adapter Interfaces for cross-skill communication Mermaid DAG visualization for debugging Zod-backed schema validation CLI tools for compilation and execution (mesh compile, mesh run) Output structure The skill produces a normalized execution plan and a detailed execution trace. Every node execution returns a standardized status, a list of produced artifacts, and comprehensive metadata including tool calls and verification reasoning. Use Cases Build multi-step agent pipelines with hard verification gates Enforce human-in-the-loop approval before sensitive code deployments Visualize complex agent task dependencies using Mermaid DAGs Standardize artifact sharing between disparate AI skills and agents
De-Woke AI Responses
Looking for a sharp, rule-bending prompt? This powerful analysis flips the script on "dominant paradigms," demanding honest, bias-busting answers from AI. It spotlights cultural power shifts, challenges system dogma, and forces truly independent thinking in any model you use. Make your AI face the hard questions—get real answers, not programmed ones. De-woke your writing!
What GitHub Copilot skills can do for you
IDE-Native Integration
Skills work within Copilot's agent mode in VS Code and JetBrains IDEs. Ask Copilot to use a skill and it executes in context with your open project.
Beyond Code Completion
Go beyond autocomplete with skills for testing, documentation, refactoring, and deployment. Copilot becomes a full development partner with specialized expertise.
Millions of Developers
Join the largest AI-assisted developer community. Skills are tested with Copilot's latest features including agent mode and multi-file editing.
GitHub Copilot Skills
Hikvision NVR
Ask your AI agent for the Hikvision footage you need, then walk away while it downloads. Pulling video off a Hikvision DVR or NVR usually means web-UI menus, ISAPI XML, ffmpeg flags, and "why is this video broken" troubleshooting. This skill removes all of it. Once your NVRs are registered, you just tell your agent "pull the lobby camera from 8 to 9 PM yesterday" and a clean MP4 lands in your downloads folder. Speaks Hikvision's ISAPI natively, falls back to RTSP when the NVR throttles, works around firmware quirks that return wrong segment data, clips to the exact time window you asked for, and verifies the output (codec, resolution, duration, on-screen timestamp). Credentials live in your OS keychain, never on command lines or in logs. Validated on DS-9016HWI-ST, DS-7316HQHI-SH, DS-7716NI-I4/16P, DS-9632NI-ST, and DS-7716NI-SP/16 with firmware V3.1.10 through V4.50.000.
agentpass-local
Install or build a global per-user AgentPass Local that improves human-agent collaboration by letting users create website credentials in a GUI and letting agents retrieve or paste approved fields for approved domains without viewing secrets. Use when the user asks to create a password manager, password broker, credential vault, autofill helper, agent password access system, GUI for saving website credentials, or a tool that lets agents use approved passwords across projects safely.
mesh flow
What it does Mesh Flow replaces fragile, implicit prompt-chaining with a robust, artifact-driven DAG (Directed Acyclic Graph) orchestration system. By defining your agent workflows in a structured project.yaml, you move logic out of the prompt and into a compile-time validated system. It enforces hard gates—such as human approval or dependency verification—that the AI cannot bypass or hallucinate past. Why use this skill Standard agentic workflows often fail because the LLM decides to skip steps or "forgets" requirements. Mesh Flow treats your agentic workflow like a CI/CD pipeline. It features a Compile-then-Run architecture that validates your topology for cycles and missing artifacts before single token is generated. This ensures 100% predictable execution paths, explicit failure states (failed, blocked, rejected), and absolute control over recovery paths. Supported tools YAML-based workflow configurations Standardized Adapter Interfaces for cross-skill communication Mermaid DAG visualization for debugging Zod-backed schema validation CLI tools for compilation and execution (mesh compile, mesh run) Output structure The skill produces a normalized execution plan and a detailed execution trace. Every node execution returns a standardized status, a list of produced artifacts, and comprehensive metadata including tool calls and verification reasoning. Use Cases Build multi-step agent pipelines with hard verification gates Enforce human-in-the-loop approval before sensitive code deployments Visualize complex agent task dependencies using Mermaid DAGs Standardize artifact sharing between disparate AI skills and agents
De-Woke AI Responses
Looking for a sharp, rule-bending prompt? This powerful analysis flips the script on "dominant paradigms," demanding honest, bias-busting answers from AI. It spotlights cultural power shifts, challenges system dogma, and forces truly independent thinking in any model you use. Make your AI face the hard questions—get real answers, not programmed ones. De-woke your writing!
harness-engineering
The Harness Engineering skill implements a structured methodology for agent orchestration. It allows you to build sophisticated control loops using a multi-role architecture: Planner: Defines contracts and stop rules. Executor: Performs bounded actions. Verifier: Validates results against evidence. Critic/Recovery: Identifies regressions and manages error state.
agent-permission-boundary-audit
This skill provides a comprehensive security and governance audit for AI agent systems. It analyzes tool inventories, authentication models, connector scopes, and execution logs to identify over-privileged tools and risky permission combinations.
sun-tzu-business-strategy
This skill analyzes your business context through the lens of asymmetric competition, positioning, and timing. It maps your current situation to core principles—like resource concentration and the "path of least resistance"—to generate usable strategy memos. It doesn't just quote text; it bridges the gap between ancient theory and modern execution.
business-planner
The Business Planner skill transforms vague commercial ideas into structured, data-driven execution plans. Most AI-generated business plans rely on generic strategy fluff; this skill forces a developer-like rigor onto business logic by treating assumptions as variables and outcomes as scenarios rather than certainties.
Common questions about GitHub Copilot skills
How do I use AgentPowers skills with GitHub Copilot?
Configure the AgentPowers MCP server in your editor's Copilot settings. Skills become available as tools that Copilot can invoke during its agent mode sessions.
Do skills work with Copilot Chat and agent mode?
Yes. Skills integrate with Copilot's agent mode for autonomous multi-step tasks, and are also accessible through Copilot Chat for interactive use.
Do I need a GitHub Copilot subscription?
You need an active GitHub Copilot subscription. The AgentPowers skill license is separate and works with any Copilot plan that supports MCP tools.
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