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Found 2,169 Skills
Design, create, and configure orq.ai Agents with tools, instructions, knowledge bases, and memory stores. Use when building new agents, attaching KBs or memory, writing system instructions, selecting models, or setting up RAG pipelines. Do NOT use for debugging existing agents (use analyze-trace-failures) or comparing agents across frameworks (use compare-agents).
Manage context-mode GitHub issues, PRs, releases, and marketing with parallel subagent army. Orchestrates 10-20 dynamic agents per task. Use when triaging issues, reviewing PRs, releasing versions, writing LinkedIn posts, announcing releases, fixing bugs, merging contributions, validating ENV vars, testing adapters, or syncing branches.
Use Gizmo to create, inspect, edit, validate, and automate browser 3D worlds with the gizmo CLI, live sessions, MCP, screenshots, component schemas, module authoring, and stable entity IDs. Use when working with Gizmo worlds, setting up agents for Gizmo, or generating 3D scenes through CLI/MCP workflows.
The full lifecycle for agentic loops — recurring, scheduled AI agents packaged as a portable LOOP.md (the agenticloops.dev standard: a trigger + skills + a prompt in one file any harness can install and run on a schedule). Use this whenever the user wants to FIND, INSTALL, RUN, or BUILD a loop: "find a loop for X", "is there a loop that…", "install a recurring agent that does X", "run this loop", as well as "create a loop", "make an agentic loop", "write a LOOP.md", "turn this into a recurring agent", "schedule an agent", "set up a cron job for an agent", or any description of a repeating job they want an agent to do on a timer (a daily digest, a competitor watcher, a triage sweep, a report pipeline, "email me X every morning", "check Y every hour") — even if they never say the word "loop". Always search the directory first and install an existing loop when one fits; author a new LOOP.md only when nothing does. This is the loop-level analogue of skill-creator + find-skills combined. For an ad-hoc in-session multi-agent run (spawn, verify, panel, fan-out) use the `loops` skill instead; for authoring a reusable SKILL.md use skill-creator.
Use for authorized security assessment of LLM applications and AI agents, including prompt injection, tool abuse, RAG exposure, memory poisoning, and model supply-chain risks.
Integrate and unbind OpenViking long-term memory with coding agents running in bwrap sandboxes. Supports 7 agents (CodeArts CLI, OpenCode, OpenClaw, Hermes, JiuwenSwarm, KimiCode, DeepSeek Harness) via their native mechanism — MCP or HTTP memory provider. Both integration and unbinding require explicit user authorization. Use this skill when the user wants to: (1) integrate OpenViking memory into a coding agent, (2) unbind OpenViking from a coding agent, (3) check the integration status of all agents, (4) verify the OpenViking MCP endpoint, (5) rebuild the OpenClaw sandbox to apply template changes. Trigger words: "OpenViking integration", "agent memory binding", "MCP setup", "OpenViking MCP", "integrate OpenViking", "unbind OpenViking", "记忆集成", "记忆解绑", "OpenViking 集成", "OpenViking 解绑", "agent long-term memory", "context database".
AI SDK 6 Beta overview, agents, tool approval, Groq (Llama), and Vercel AI Gateway. Key breaking changes from v5 and new patterns.
AI-agent readiness auditing for project documentation and workflows. Evaluates whether future Claude Code sessions can understand docs, execute workflows literally, and resume work effectively. Use when onboarding AI agents to a project or ensuring context continuity. Includes three specialized agents: context-auditor (AI-readability), workflow-validator (process executability), handoff-checker (session continuity). Use PROACTIVELY before handing off projects to other AI sessions or team members.
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)
Creates custom agents, workflows, and templates for BMAD. Extends BMAD functionality with domain-specific components. Trigger keywords - create agent, create workflow, custom skill, extend BMAD, new template, customize, scaffold skill
This skill provides comprehensive guidance for using OpenCode, the open-source AI coding agent. Use this skill when working with OpenCode CLI commands, keyboard shortcuts, agents (build/plan), slash commands, tools, skills, MCP servers, or configuration. Automatically triggered when OpenCode-specific questions or tasks are detected.
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications