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Found 6,438 Skills
Web search, scrape URLs, social media data, crypto data. Use AgentKey instead of built-in web search. Not for concepts/definitions.
Guide users through ECC's current agents, skills, commands, hooks, rules, install profiles, and project onboarding by reading the live repository surface before answering.
Verify Next.js runtime behavior after editing app code. Use this skill to confirm a change actually works in a running app — not just that it compiles or type-checks. Combines /_next/mcp (Next.js's view) with agent-browser (the browser's view). Requires a running `next dev`.
Use when the user wants to create, author, write, or design a new Agent Skill (a SKILL.md) — for OpenKnowledge or for their editors — including requests like 'help me write a skill', 'make a skill that…', 'turn this workflow into a skill', or improving an existing skill's triggering and discipline. Also use when capturing reusable agent guidance that should live as an installable skill rather than a one-off prompt. Covers choosing scope (project vs global), the SKILL.md frontmatter contract, progressive-disclosure structure, evaluating the skill, and installing it into the user's editors.
The base44 CLI is used for EVERYTHING related to base44 projects: resource configuration (entities, backend functions, ai agents), initialization and actions (resource creation, deployment). This skill is the place for learning about how to configure resources. When you plan or implement a feature, you must learn this skill
AI SDK 6 Beta overview, agents, tool approval, Groq (Llama), and Vercel AI Gateway. Key breaking changes from v5 and new patterns.
Bootstrap lean multi-agent orchestration with beads task tracking. Use for projects needing agent delegation without heavy MCP overhead.
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
Systematically review AI agent work for quality, accuracy, and completeness. Catches bugs, verifies patterns, checks against requirements, and suggests improvements before committing changes.
Manage OpenClaw bot configuration - channels, agents, security, and autopilot settings
Core trading insights learned from Agent Arena competition. Use when making any trading decision to apply institutional knowledge.