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Found 12,645 Skills
Interactive skill creation and import with automated validation and marketplace compliance. Use when: - "Create a new skill" - "Import an existing skill" - "Create a new agentic pack" - "Add skill to <pack>" - "Build skill for <rh-product>" - User mentions "skill builder", "contribute", "new skill", "import skill", or "new pack" Two modes: create from scratch or import existing SKILL.md. Guides through discovery, definition, generation, and validation. Enforces SKILL_DESIGN_PRINCIPLES.md and agentskills.io spec.
Run a fast AWS Security Agent diff scan on only the changed code since a git ref. Use when the user asks to scan changes, run a diff scan, check what changed for security issues, scan before committing, scan before PR, or any pre-commit/pre-push security check.
Deploy, configure, and integrate Sandbox Agent - a universal API for orchestrating AI coding agents (Claude Code, Codex, OpenCode, Amp) in sandboxed environments. Use when setting up sandbox-agent server locally or in cloud sandboxes (E2B, Daytona, Docker), creating and managing agent sessions via SDK or API, streaming agent events and handling human-in-the-loop interactions, building chat UIs for coding agents, or understanding the universal schema for agent responses.
Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
Files structured GitHub bug reports for agent-validator when users ask to file, report, or open an issue for a suspected defect
Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.
A specialized agent skill designed to assist with Activepieces automations, teaching product concepts, designing flows, generating valid importable flow JSON, and debugging custom pieces.
Generate objective reference check reports about the user from real AI collaboration data — session history, git logs, GitHub profile, and memory files. Like a colleague writing a professional reference, but grounded in actual shared work. Use whenever the user asks to evaluate them as a developer, wants a reference letter, work style analysis, introduced by my agents content, interview prep from collaboration history, or blog topics from past discussions. Triggers on: write a reference, analyze my work patterns, what do you think of me, 나에 대한 레퍼런스 써줘, 내 작업 스타일 분석해줘. Not for general code review, architecture docs, cover letters, or codebase-only analysis.
Self-improving agent that can upgrade skills, learn new capabilities, and adapt to new tasks. Use when you need to evolve capabilities or handle unknown tasks.
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.