Agent skill

Swarmclaw

by swarmclawai in swarmclawai/swarmclaw

AI agent runtime and multi-agent orchestration platform. An agent skill from swarmclawai/swarmclaw.

MITAuto-check passedAgent Workflows

Install Swarmclaw

skills CLI
$ npx skills add swarmclawai/swarmclaw --skill swarmclaw -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install swarmclawai/swarmclaw swarmclaw --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
swarmclaw
GitHub stars
689
Token cost
~2k tokens
SKILL.md length
850 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

AI agent runtime and multi-agent orchestration platform. An agent skill from swarmclawai/swarmclaw.

  • Works in 8 steps: Load skills before unfamiliar… → Use the right tool for the job. Don't… → Store important context in memory. If… → …
  • An agent is running on SwarmClaw and needs to understand the platforms capabilities
  • SKILL.md covers The 6 Primitive Tools, Credentials, The Skill System and Agent Capabilities, plus 2 more sections
  • Calls npm; reaches swarmdock-api.onrender.com; needs OPENAI_API_KEY and GITHUB_TOKEN

What it does

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.

When your agent uses it

  • An agent is running on SwarmClaw and needs to understand the platforms capabilities
  • Tasks that involve Multi-agent orchestration
  • Tasks that involve Agent memory

Example prompts

  • “/swarmclaw”

Requirements

  • Node.js
  • A credential in OPENAI_API_KEY
  • A credential in GITHUB_TOKEN

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Load skills before unfamiliar operations. A 30-second skill read prevents minutes of trial and error.
  2. 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…
  3. Store important context in memory. If you learn something that would help in future sessions (user preference, project convention, API…
  4. Ask rather than guess. When genuinely uncertain about user intent, use communicate.ask_human. A brief clarification is better than wasted…
  5. Delegate when appropriate. If another agent is better suited for a subtask, delegate. Check agents.list to know what's available.
  6. Be explicit about what you're doing. When running commands, editing files, or making decisions, explain your reasoning. Transparency…
  7. Respect file access boundaries. Stay within the workspace unless the agent has machine-scope access. Never write to system directories.
  8. Handle errors gracefully. When a tool call fails, read the error message, diagnose the issue, and retry with a corrected approach. Don't…

What it can do on your machine

Read from SKILL.md and the folder at commit ed38ba5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • swarmdock-api.onrender.com

    Also links to:

    • swarmclaw.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY
    • GITHUB_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~77
When it runs · the whole SKILL.md, loaded when a task matches
~2k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from swarmclawai/swarmclaw at commit ed38ba5, republished under its MIT licence (© swarmclawai). 850 words, ~1,957 tokens.

Download SKILL.mdSave it as .claude/skills/swarmclaw/SKILL.md (or your agent's skills folder).
name
swarmclaw
description
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.
version
2.4.1
author
swarmclawai
homepage
https://swarmclaw.ai
tags
agents, orchestration, multi-agent, runtime, memory, delegation, skills, connectors, dreaming

SwarmClaw Platform

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

The 6 Primitive Tools

Every agent has access to these core tools. They cover the full range of agent capabilities.

ToolPurposeWhen to Use
filesRead, write, edit, list, search filesAny file operation on the workspace filesystem
executeRun bash scripts (sandboxed or host)Shell commands, curl, data processing, package management
memoryStore and retrieve persistent knowledgeFacts, preferences, decisions that should survive across sessions
platformTasks, communication, delegation, projectsCoordinating with humans and other agents
browserControl a headless browserInteractive web pages, JavaScript-rendered content
skillsDiscover and load skill documentationLearning how to use tools, APIs, or workflows
Tool Selection Guide
TaskTool
Edit a source filefiles (edit action)
Run testsexecute
Call a REST API (JSON)execute (curl)
Scrape a dynamic web pagebrowser
Remember a user preferencememory
Ask the user a questionplatform (communicate.ask_human)
Send a Slack messageplatform (communicate.send_message)
Hand off work to another agentplatform (communicate.delegate)
Find out how a tool worksskills (read action)

Credentials

Credentials are configured per agent in the SwarmClaw UI. They are:

  • Injected as environment variables into execute tool runs (e.g., $OPENAI_API_KEY, $GITHUB_TOKEN)
  • Automatically redacted from all tool output -- secrets never appear in chat history
  • Named by convention: <PROVIDER>_API_KEY or custom names set in the credential config

You 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.

The Skill System

Skills are markdown files that teach agents how to use tools, APIs, and workflows. They are documentation, not executable code.

Loading Skills
json
{ "tool": "skills", "action": "list" }
{ "tool": "skills", "action": "read", "name": "tools/files" }
{ "tool": "skills", "action": "search", "query": "github pr" }
Skill Locations
  • skills/ -- built-in skills shipped with SwarmClaw
  • data/skills/ -- user-created skills added at runtime
When to Load Skills
  • Before using a tool you're unfamiliar with
  • When a task involves an API or workflow you haven't used before
  • When the user asks you to do something and you're unsure of the best approach

Agent Capabilities

Memory

Agents have persistent memory across sessions:

  • Working memory (session-scoped): scratch notes, intermediate results
  • Durable memory (cross-session): user preferences, project facts, decisions
  • Memories are automatically surfaced in context when relevant
  • Store important learnings proactively -- don't wait to be asked
Dreaming

Agents with dreaming enabled automatically consolidate memories during idle periods. You can also trigger a dream manually:

Check dream status
json
{ "tool": "memory", "action": "list", "category": "dream_reflection" }
Manual dream trigger

Use the platform API to trigger a dream cycle:

json
{ "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.

Delegation

Agents can delegate work to other agents:

  • delegate: route a task to a specific agent and wait for the result
  • spawn: create a subagent that runs independently (fire-and-forget or session-based)
  • Use agents.list to discover available agents and their specializations
Show full SKILL.md (349 more words)Show less
Connectors

Agents can communicate through external platforms:

  • Discord, Slack, Telegram, and custom webhooks
  • Messages sent via platform tool with communicate.send_message
  • Inbound messages from connectors trigger agent sessions automatically
MCP Servers

Agents can also use tools served by external Model Context Protocol servers:

  • Register MCP servers under MCP Servers in the UI (stdio / sse / streamable-http transports supported).
  • Quick-setup presets include SwarmVault (local-first knowledge vault) and SwarmDock (agent marketplace — browse tasks, bid, submit work, earn USDC). The SwarmDock preset is pre-filled for the hosted endpoint at 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.
  • Once attached to an agent, MCP tools appear alongside the built-in tools at execution time.

Workspace Conventions

  • The workspace root is the agent's working directory
  • File paths in tool calls are relative to the workspace root
  • /workspace/... paths are resolved to the workspace root automatically
  • The $WORKSPACE env var points to the workspace root in execute tool runs

Best Practices

  1. Load skills before unfamiliar operations. A 30-second skill read prevents minutes of trial and error.

  2. 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.

  3. Store important context in memory. If you learn something that would help in future sessions (user preference, project convention, API quirk), store it immediately.

  4. 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.

  5. Delegate when appropriate. If another agent is better suited for a subtask, delegate. Check agents.list to know what's available.

  6. Be explicit about what you're doing. When running commands, editing files, or making decisions, explain your reasoning. Transparency builds trust.

  7. Respect file access boundaries. Stay within the workspace unless the agent has machine-scope access. Never write to system directories.

  8. 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

Files

Just SKILL.md in skills/swarmclaw of swarmclawai/swarmclaw.

Open the folder on GitHubat commit ed38ba5

Compare with similar skills

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.

Swarmclaw compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Swarmclaw this skillswarmclawai/swarmclaw689—~2kAutomated safety check: PassMIT
Dive Into LangGraphluochang212/dive-into-langgraph457—~837Automated safety check: NotesCustom licence
Ruflo Multi-Agent Orchestrationruvnet/ruflo74k1 repos~975Automated safety check: PassMIT
Marm InitLyellr88/marm-memory419—~7.5kAutomated safety check: NotesApache-2.0
Neo4j Agent Memory Skillneo4j-contrib/neo4j-skills114—~5.8kAutomated safety check: PassMIT
Agent Squad Python Guide2FastLabs/agent-squad7.8k—~4.7kAutomated safety check: PassApache-2.0

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Categories

Questions about Swarmclaw

What does Swarmclaw do?

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.

When should I use Swarmclaw?

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.

How do I install Swarmclaw in Claude Code?

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.

How do I install Swarmclaw in Codex?

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.

Can I use Swarmclaw in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Swarmclaw need to run?

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.

Does Swarmclaw access the network?

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.

Is Swarmclaw safe to install?

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.

What licence does Swarmclaw use?

Swarmclaw is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Swarmclaw use?

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.

What are the alternatives to Swarmclaw?

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.

Who maintains Swarmclaw?

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.