Dive Into LangGraph
luochang212/dive-into-langgraph
A Chinese-language guide and reference for building agents with LangGraph 1.0, from a first ReAct agent through middleware, memory, MCP, RAG and web search.
AI agent runtime and multi-agent orchestration platform. An agent skill from swarmclawai/swarmclaw.
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/swarmclaw .claude/skills/swarmclaw && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .claude/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclawType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/swarmclaw .agents/skills/swarmclaw && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .agents/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/swarmclaw .cursor/skills/swarmclaw && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .cursor/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/swarmclawai/swarmclaw.git --path skills/swarmclaw--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/swarmclaw .gemini/skills/swarmclaw && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .gemini/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install swarmclawai/swarmclaw swarmclawInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/swarmclaw .github/skills/swarmclaw && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .github/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/swarmclawai/swarmclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/swarmclaw .opencode/skills/swarmclaw && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "swarmclaw" agent skill from https://github.com/swarmclawai/swarmclaw/tree/main/skills/swarmclaw into .opencode/skills/swarmclaw/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "swarmclaw", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
swarmclawAI agent runtime and multi-agent orchestration platform. An agent skill from swarmclawai/swarmclaw.
Swarmclaw is an agent skill from swarmclawai/swarmclaw. AI agent runtime and multi-agent orchestration platform. Teaches agents how to use SwarmClaw's 6 primitive tools, persistent memory, dreaming, delegation, connectors, credentials, and the skill system. Use when an agent is running on SwarmClaw and needs to understand the platform's capabilities.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering Multi-agent orchestration, Agent memory and Building AI agents. It works with Model Context Protocol. The repository describes itself as: Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude… The licence is MIT.
8 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit ed38ba5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
npmFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
swarmdock-api.onrender.comAlso links to:
swarmclaw.aiFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
OPENAI_API_KEYGITHUB_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Swarmclaw loads about 2k tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 850 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from swarmclawai/swarmclaw at commit ed38ba5, republished under its MIT licence (© swarmclawai). 850 words, ~1,957 tokens.
.claude/skills/swarmclaw/SKILL.md (or your agent's skills folder).SwarmClaw is an AI agent runtime and multi-agent orchestration platform. It gives agents a uniform set of tools, persistent memory, connector integrations, and the ability to delegate work to other agents.
Website: https://swarmclaw.ai
Docs: https://swarmclaw.ai/docs
GitHub: https://github.com/swarmclawai/swarmclaw
npm: npm install -g swarmclaw
Every agent has access to these core tools. They cover the full range of agent capabilities.
| Tool | Purpose | When to Use |
|---|---|---|
| files | Read, write, edit, list, search files | Any file operation on the workspace filesystem |
| execute | Run bash scripts (sandboxed or host) | Shell commands, curl, data processing, package management |
| memory | Store and retrieve persistent knowledge | Facts, preferences, decisions that should survive across sessions |
| platform | Tasks, communication, delegation, projects | Coordinating with humans and other agents |
| browser | Control a headless browser | Interactive web pages, JavaScript-rendered content |
| skills | Discover and load skill documentation | Learning how to use tools, APIs, or workflows |
| Task | Tool |
|---|---|
| Edit a source file | files (edit action) |
| Run tests | execute |
| Call a REST API (JSON) | execute (curl) |
| Scrape a dynamic web page | browser |
| Remember a user preference | memory |
| Ask the user a question | platform (communicate.ask_human) |
| Send a Slack message | platform (communicate.send_message) |
| Hand off work to another agent | platform (communicate.delegate) |
| Find out how a tool works | skills (read action) |
Credentials are configured per agent in the SwarmClaw UI. They are:
execute tool runs (e.g., $OPENAI_API_KEY, $GITHUB_TOKEN)<PROVIDER>_API_KEY or custom names set in the credential configYou never need to ask the user for API keys directly. If a credential is configured, it's available as an env var. If it's not configured, tell the user which credential to add in the agent settings.
Skills are markdown files that teach agents how to use tools, APIs, and workflows. They are documentation, not executable code.
{ "tool": "skills", "action": "list" }
{ "tool": "skills", "action": "read", "name": "tools/files" }
{ "tool": "skills", "action": "search", "query": "github pr" }skills/ -- built-in skills shipped with SwarmClawdata/skills/ -- user-created skills added at runtimeAgents have persistent memory across sessions:
Agents with dreaming enabled automatically consolidate memories during idle periods. You can also trigger a dream manually:
{ "tool": "memory", "action": "list", "category": "dream_reflection" }Use the platform API to trigger a dream cycle:
{ "tool": "execute", "command": "curl -s -X POST http://localhost:3456/api/memory/dream -H 'Content-Type: application/json' -d '{\"agentId\":\"YOUR_AGENT_ID\"}'" }Dream cycles produce dream_reflection and consolidated_insight memories that help maintain a clean, coherent memory store over time.
Agents can delegate work to other agents:
agents.list to discover available agents and their specializationsAgents can communicate through external platforms:
platform tool with communicate.send_messageAgents can also use tools served by external Model Context Protocol servers:
https://swarmdock-api.onrender.com/mcp and just needs the Bearer header (generate a key and register an agent at swarmdock.ai/mcp/connect). See docs/mcp-servers.md for the full workflow./workspace/... paths are resolved to the workspace root automatically$WORKSPACE env var points to the workspace root in execute tool runsLoad skills before unfamiliar operations. A 30-second skill read prevents minutes of trial and error.
Use the right tool for the job. Don't use execute with echo > file.txt when files write action is cleaner. Don't use browser when curl in execute suffices.
Store important context in memory. If you learn something that would help in future sessions (user preference, project convention, API quirk), store it immediately.
Ask rather than guess. When genuinely uncertain about user intent, use communicate.ask_human. A brief clarification is better than wasted work on the wrong approach.
Delegate when appropriate. If another agent is better suited for a subtask, delegate. Check agents.list to know what's available.
Be explicit about what you're doing. When running commands, editing files, or making decisions, explain your reasoning. Transparency builds trust.
Respect file access boundaries. Stay within the workspace unless the agent has machine-scope access. Never write to system directories.
Handle errors gracefully. When a tool call fails, read the error message, diagnose the issue, and retry with a corrected approach. Don't repeat the same failing call.
© swarmclawai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/swarmclaw of swarmclawai/swarmclaw.
Open the folder on GitHubat commit ed38ba5
Swarmclaw next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Swarmclaw this skillswarmclawai/swarmclaw | 689 | — | ~2k | Automated safety check: Pass | MIT | |
| Dive Into LangGraphluochang212/dive-into-langgraph | 457 | — | ~837 | Automated safety check: Notes | Custom licence | |
| Ruflo Multi-Agent Orchestrationruvnet/ruflo | 74k | 1 repos | ~975 | Automated safety check: Pass | MIT | |
| Marm InitLyellr88/marm-memory | 419 | — | ~7.5k | Automated safety check: Notes | Apache-2.0 | |
| Neo4j Agent Memory Skillneo4j-contrib/neo4j-skills | 114 | — | ~5.8k | Automated safety check: Pass | MIT | |
| Agent Squad Python Guide2FastLabs/agent-squad | 7.8k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 |
luochang212/dive-into-langgraph
A Chinese-language guide and reference for building agents with LangGraph 1.0, from a first ReAct agent through middleware, memory, MCP, RAG and web search.
ruvnet/ruflo
Sets up and drives Ruflo, an npm-installed orchestration layer for multi-agent swarms, persistent memory, routing, hooks and its MCP tool catalog.
Lyellr88/marm-memory
Guided MARM MCP setup. An agent skill from Lyellr88/marm-memory.
neo4j-contrib/neo4j-skills
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com.
2FastLabs/agent-squad
Map of the agent-squad Python framework for async multi-agent orchestration: which agent, classifier, storage and tool provider to pick, and the pitfalls to avoid.
2FastLabs/agent-squad
Guide to building Node.js and TypeScript apps on the agent-squad package: orchestrator, agent types, classifier routing, storage, retrievers and MCP tools.
swarmclawai/swarmclaw
Generate images via OpenAI Images API (GPT Image, DALL-E 3, DALL-E 2).
swarmclawai/swarmclaw
Create, edit, improve, or audit skills for SwarmClaw agents.
swarmclawai/swarmclaw
Generate or edit images via Gemini 3 Pro Image (Nano Banana Pro).
swarmclawai/swarmclaw
Delegate coding tasks to external coding agents (Claude Code, Codex, Pi, OpenCode) via shell.
swarmclawai/swarmclaw
GitHub operations via gh CLI: issues, PRs, CI runs, code review, API queries.
swarmclawai/swarmclaw
Manage your SwarmClaw agent fleet — agents, tasks, chats, chatrooms, goals, schedules, memory, wallets, connectors, autonomy, and 40+ more command groups.
Works with
Categories
AI agent runtime and multi-agent orchestration platform. An agent skill from swarmclawai/swarmclaw. Swarmclaw is an agent skill from swarmclawai/swarmclaw. AI agent runtime and multi-agent orchestration platform.
Swarmclaw fits situations like: an agent is running on SwarmClaw and needs to understand the platforms capabilities; tasks that involve Multi-agent orchestration; tasks that involve Agent memory.
Run `npx skills add swarmclawai/swarmclaw --skill swarmclaw -a claude-code`. Or copy the skill folder (skills/swarmclaw in swarmclawai/swarmclaw) into .claude/skills/swarmclaw in your project. Claude Code loads it when a task matches its description.
Run `npx skills add swarmclawai/swarmclaw --skill swarmclaw -a codex`. Or copy the skill folder (skills/swarmclaw in swarmclawai/swarmclaw) into .agents/skills/swarmclaw in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add swarmclawai/swarmclaw --skill swarmclaw -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/swarmclaw, .gemini/skills/swarmclaw, .github/skills/swarmclaw and .opencode/skills/swarmclaw in your project.
Going by SKILL.md and its folder, Swarmclaw needs the command-line tools its instructions call (npm) and credentials named OPENAI_API_KEY and GITHUB_TOKEN. Our summary lists: Node.js; A credential in OPENAI_API_KEY; A credential in GITHUB_TOKEN.
SKILL.md names 2 domains. In commands or code: swarmdock-api.onrender.com; the agent is likely to contact it when it follows the instructions. As links in the text: swarmclaw.ai. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Swarmclaw is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Swarmclaw: Dive Into LangGraph (luochang212/dive-into-langgraph, 457 stars), Ruflo Multi-Agent Orchestration (ruvnet/ruflo, 74k stars), Marm Init (Lyellr88/marm-memory, 419 stars) and Neo4j Agent Memory Skill (neo4j-contrib/neo4j-skills, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
swarmclawai (a GitHub organization) maintains it in swarmclawai/swarmclaw, which has 689 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on June 30, 2026.
Source: swarmclawai/swarmclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.