智能体
Agent 规划、多步流程与编排
nelson
kylesnowschwartz
This skill SHOULD be used when work requires multi-agent coordination, parallel execution, or structured team workflows. Commands a Royal Navy agent squadron from sailing orders through execution and stand-down with risk-tiered quality gates and a captain's log.
sc-think-functional
kylesnowschwartz
Reframe code design through functional programming principles for agent-assisted development. This skill SHOULD be used when the user says "think functional", "think FP", "make this pure", "separate effects", "where should this side effect go", "this function does too much", "how should I structure this for agents", "make this easier to review", "reduce context needed", or when planning module structure, store design, or code that agents will write and humans will review. Applies FP discipline within any language to maximize agent effectiveness and human reviewability.
auto-trigger
zhaono1
Workflow automation hooks for agent-playbook skills. This skill defines automatic triggers between skills - DO NOT use directly, it's a configuration skill that other skills reference.
agent-browser-3
sundial-org
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
agent-orchestrator
sundial-org
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks
agentic-compass
sundial-org
Top OpenClaw skills, with the most popular and useful ones.
deepthink
solatis
Invoke IMMEDIATELY via python script when user requests structured reasoning for open-ended analytical questions. Do NOT explore first - the script orchestrates the thinking workflow.
planning-context-resolver
OmniNode-ai
Read-only intelligence agent that compiles structured planning context for an epic
deepagents-planning-todos
Lubu-Labs
Use the write_todos tool effectively for task planning and decomposition in Deep Agents. Use when users want to (1) implement task planning with write_todos, (2) break down complex tasks into subtasks, (3) track agent progress through todos, (4) debug why todos aren't completing, (5) design todo structures for different task types (research, coding, analysis), (6) understand todo status lifecycle and best practices, or (7) visualize todo progression from LangSmith traces.
langgraph-agent-patterns
Lubu-Labs
Implement multi-agent coordination patterns (supervisor-subagent, router, orchestrator-worker, handoffs) for LangGraph applications. Use when users want to (1) implement multi-agent systems, (2) coordinate multiple specialized agents, (3) choose between coordination patterns, (4) set up supervisor-subagent workflows, (5) implement router-based agent selection, (6) create parallel orchestrator-worker patterns, (7) implement agent handoffs, (8) design state schemas for multi-agent systems, or (9) debug multi-agent coordination issues.
architect
uze-sh
Writing and changing the Mermaid diagrams a project keeps under artifacts: — choosing which diagram and which level a change belongs in, naming it so it reads where a reader expects, and proving it still draws with uze agent artifacts check, which needs no workspace. Use when adding or editing a .mmd/.mermaid file, when asked to diagram or document an architecture, when a diagram does not draw, or when setting up where a project keeps its architecture.
langgraph-project-setup
Lubu-Labs
Initialize and configure LangGraph projects with proper structure, langgraph.json configuration, environment variables, and dependency management. Use when users want to (1) create a new LangGraph project, (2) set up langgraph.json for deployment, (3) configure environment variables for LLM providers, (4) initialize project structure for agents, (5) set up local development with LangGraph Studio, (6) configure dependencies (pyproject.toml, requirements.txt, package.json), or (7) troubleshoot project configuration issues.
deepagents-setup-configuration
Lubu-Labs
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the deepagents package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from create_react_agent or create_agent, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
langsmith-deployment
Lubu-Labs
"Deploy and operate production agent servers with LangSmith Deployment. Use when work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone, preparing/validating langgraph.json, creating deployments or revisions, rolling back revisions, wiring CI/CD to control-plane APIs, configuring environment variables and secrets, setting monitoring/alerts/webhooks, or troubleshooting deployment/runtime/scaling issues for LangChain/LangGraph applications."
decompose-epic
OmniNode-ai
Analyze a Linear epic description and create sub-tickets as Linear children
golden-path-validate
OmniNode-ai
Execute a golden path event chain test using real Kafka/Redpanda to validate end-to-end event flows
langgraph-state-management
Lubu-Labs
Design state schemas, implement reducers, configure persistence, and debug state issues for LangGraph applications. Use when users want to (1) design or define state schemas for LangGraph graphs, (2) implement reducer functions for state accumulation, (3) configure persistence with checkpointers (InMemorySaver/MemorySaver, SqliteSaver, PostgresSaver), (4) debug state update issues or unexpected state behavior, (5) migrate state schemas between versions, (6) validate state schema structure, (7) choose between TypedDict and MessagesState patterns, (8) implement custom reducers for lists, dicts, or sets, (9) use the Overwrite type to bypass reducers, (10) set up thread-based persistence for multi-turn conversations, or (11) inspect checkpoints for debugging.
architect-refine-critique
NTCoding
"Three-phase design review. Chain architect → refiner → critique subagents. Triggers on: 'design review', 'architecture review', '/arc', system design proposals, significant refactoring decisions, new service or module design."
paperjury
u7079256
Three modes for CS-conference papers (CVPR/ICCV/ECCV vision, ACL/EMNLP/NAACL NLP, ICLR/NeurIPS/ICML/AAAI ML). DIRECT-EDIT mode (common): the user describes a change in Chinese or English and the LaTeX is edited directly through a CS-venue writing toolkit with author sign-off (use for 改这段 / 把中文想法写成 latex / polish / de-AI / translate / compress a passage). REVIEW mode (occasional, pre-submission): harden the paper through an adversarial courtroom review engine (N holistic domain reviewers / contestability routing / two-sided trial / three-way verdict / clerk-converged multi-round loop) with consensus-gated, author-signed revisions (use for review / critique / 审稿 / 评审 / mock-review). AUTO mode (unattended, opt-in via /goal): run the review-revise loop toward a verifiable goal, applying safe fixes under a drift-bounded policy and queueing risky ones. Resolves all inputs at runtime, no hardcoded paths. Not a from-scratch drafter (use ml-paper-writing) and not an official-venue rebuttal.
agent-browser-5
sundial-org
A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
agentCreate
LeoYeAI
"AI-powered OpenClaw agent creator. 用AI创作AI - 帮助用户创建和配置全新的独立agent，支持飞书机器人绑定、模型选择、工作区配置。Trigger: 创建agent、new agent、创建机器人、agent setup、new bot、卸载agent、删除agent、remove agent"
agentbay-monitor-skills
agentbay-ai
舆情监控技能，最终产出舆情报告。当用户问「某事件/话题舆情如何」「舆论怎么样」「做舆情分析」「运行舆情分析」或按关键词/平台爬取并生成舆情报告时，使用本技能。约定：凡舆情相关意图即执行全流程（爬取→情感分析→生成报告）。爬取由本技能完成；情感分析由主 Agent 按提示词自主判断；报告由 generate_report 生成。
Iterm2
julianobarbosa
iTerm2 terminal emulator and tmux multiplexer expertise. USE WHEN user mentions iTerm2, tmux, terminal sessions, split panes, window management, OR terminal productivity on macOS.
az-aks-agent
julianobarbosa
Azure AKS Agentic CLI - AI-powered troubleshooting and insights tool for Azure Kubernetes Service. Use when diagnosing AKS cluster issues, getting cluster health insights, troubleshooting networking/storage/security problems, or analyzing cluster configuration with natural language queries.