Loading...
Loading...
Found 118 Skills
Orchestrate a specialized software development agent team. Receive user requests, classify task type, select the matching workflow, delegate each step to specialist agents via the Agent tool, and assemble the final output. Use when the user needs multi-step software development involving architecture, implementation, testing, security review, or code review. Also use for production incident investigation — when the user reports a live system issue, service outage, pod crash, data anomaly, or needs root cause analysis using kubectl, psql, argocd, or docker. Trigger this skill whenever a task involves more than one concern (e.g., "add a new endpoint" needs BA + Architect + Developer + QA + Security), when the user mentions team coordination, agent delegation, or when the work clearly benefits from multiple specialist perspectives rather than a single implementation pass.
Agent skill for consensus-coordinator - invoke with $agent-consensus-coordinator
Expert in making multi-agent systems resilient. Specializes in detecting loops, hallucinations, and failures, and implementing self-healing workflows. Use when designing error handling for agent systems, implementing retry strategies, or building resilient AI workflows.
Review a single file or all files in a folder for data inconsistencies, reference errors, typos, and unclear terminology using parallel sub-agents
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
Build specialized openclaw agents with proper workspace structure, identity, and skills
The slogan unpacked — seven readings of 'Manufacturing Intelligence'
Open a new context session at the start of a leader agent workflow. Records agentName, storyId, and phase in wint.contextSessions, emitting a structured SESSION CREATED block for downstream workers to inherit.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Turns a free-form project description into PROJECT_MANIFEST.md and SOFTWARE_FACTORY_MANIFEST.md for a 6-agent software factory pipeline. Agent-agnostic: works in Claude Code, Codex CLI, Gemini CLI.
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.