clawsomeflow 0.1.8

Vertical agent workflow orchestration platform on top of ClawTeam and OpenClaw

⚡ ClawsomeFlow ⚡

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Describe your goal in natural language, and turn multi-agent collaboration into a controllable, observable, convergent engineering system.

ClawsomeFlow is a vertical-domain Agent workflow orchestration platform: define tasks as a DAG Flow, and let an async scheduler actively drive multiple Agents to collaborate in parallel, with built-in engineering guardrails such as isolation / rollback / complaint-loop / entropy management.

Full compatibility with OpenClaw, Claude Code, Codex, Cursor, Hermes and other CLI Agents.

Quick Start · News · Core Features · Why ClawsomeFlow · Contributor Local Deploy · Roadmap · WeChat Community

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📰 News

• 2026-06-02: ClawsomeFlow public release 🎉

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✨ Core Features

Building on top of ClawTeam's swarm-intelligence capabilities, ClawsomeFlow adds the two missing engineering layers — orchestration + product:

🌳 Deep OpenClaw Adaptation	🧠 AI + Precise Orchestration	🗣️ Get Everything Done in Natural Language	🔄 Complaint-Loop Mechanism
For OpenClaw's blurry session boundaries and workspace concurrency conflicts under multi-task parallelism, we apply dual session-and-directory isolation and fold recovery paths into a standard state machine.	Take control flow back from the Prompt into code: the scheduler decides dispatch, retry, timeout and convergence — behavior is controllable, with significantly fewer wasted tokens.	Flow definition, Agent creation, task orchestration, and runtime intervention can all be done in natural language via the Web UI / CLI.	A Run supports the "user complaint → reflective processing → write back experience" loop, so the system keeps self-improving.

🚀 Multi-Agent Collaboration	📊 Enterprise-Grade Observability	🔐 Isolation & Governance Together	🧩 Compatible with Existing Ecosystems
Supports OpenClaw / Claude / Codex / Cursor / Hermes collaborating in the same graph.	Every dispatch / completion / failure is recorded as a RunEvent — auditable, replayable, billable.	Three-layer isolation across team / session / worktree, avoiding cross-talk and accidental writes.	We don't reinvent the protocol layer; we reuse ClawTeam CLI + MCP and its swarm collaboration and monitoring.

🦞 The Swarm-Intelligence Foundation Inherited from ClawTeam

ClawsomeFlow stands on the shoulders of ClawTeam, faithfully inheriting its swarm-collaboration core:

• Self-organizing Agent collaboration: the Leader dispatches, Workers self-report status and results, CLI Agents are plug-and-play with no custom SDK required.
• Git Worktree workspace isolation: each Agent has an independent branch and directory, running in parallel without interference, with checkpoint / merge / cleanup support.
• Inter-Agent messaging: point-to-point inbox and broadcast, so team members share progress in real time.

On top of this, ClawsomeFlow layers in deep OpenClaw adaptation, DAG orchestration scheduling, failure convergence, human guardrails, Web productization and multi-user governance.

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🤖 Supported Agents

Agent	Kind	Runtime	Status
OpenClaw	openclaw	TUI	⭐ Deeply adapted
Claude Code	claude	TUI	✅ Full support
Codex	codex	TUI	✅ Full support
Gemini CLI	gemini	TUI	Testing
Cursor	cursor	TUI	✅ Full support
Hermes	hermes	TUI	✅ Full support
Kimi CLI	kimi	TUI	Testing
Qwen Code	qwen	TUI	Testing
OpenCode	opencode	TUI	Testing
nanobot	nanobot	TUI	Testing

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🤔 Why ClawsomeFlow?

The common pain point of multi-agent frameworks is not "insufficient model capability", but "unstable collaboration control flow": the process is written in the Prompt, the final behavior depends on the Agent's in-the-moment understanding and model quality, and the system's predictability, cost and recoverability are all too weak.

ClawsomeFlow's approach is direct: migrate coordination from natural language back into code, make concurrency isolation a default capability, and make failure handling a built-in part of the process.

🆚 Comparison with Other Agent Orchestration Platforms

Dimension	Other Multi-Agent Orchestration Platforms	✅ ClawsomeFlow
Task orchestration fit	Mostly framework-specific, bound to a single ecosystem	Task orchestration is deeply adapted to OpenClaw Agents, while also being compatible with any CLI Agent (Claude / Codex / Cursor, etc.) collaborating in the same graph
Concurrency & isolation	Easy contention in parallel, workspace conflicts, context cross-talk	Solves OpenClaw collaboration instability: workspace isolation and rollback under multi-task parallelism, and thoroughly resolves session conflicts
Control approach	Pure Prompt self-scheduling (black box) or pure code (heavy)	AI combined with precise orchestration: get everything done in natural language while the scheduler precisely controls behavior (dispatch / retry / timeout / abort)
Engineering harness	Generally missing; failures rely on Agent improvisation	Harness engineering: human checkpoints, rollbackable results, complaint-loop mechanism, periodic entropy management
Failure recovery	Relies on Agent self-healing, uncertain outcome	Clear retry / skip / abort strategies, recovery paths folded into a standard state machine
Observability	Context is mostly a black box	Full-chain RunEvent — traceable, auditable, replayable

✨ The Result?

You own the goal, and ClawsomeFlow turns multi-agent collaborative execution into a stable, controllable, convergent engineering system.

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🧩 Relationship with ClawTeam

ClawsomeFlow is built on top of ClawTeam.

🔍 ClawTeam vs ClawsomeFlow at a Glance

Dimension	ClawTeam	ClawsomeFlow
Positioning	Swarm-intelligence protocol foundation (Agent self-organization)	Agent workflow orchestration platform
Collaboration driver	Agents self-poll and self-schedule in the Prompt	Server-side scheduler actively dispatches, deterministic execution
Task model	Kanban + dependency chain	DAG Flow compilation, Leader summarizes and converges
OpenClaw adaptation	Supported as an optional CLI Agent	Deeply adapted, resolving session and workspace concurrency conflicts
Failure & guardrails	Basic lifecycle protocol	Human checkpoints / rollback / complaint-loop / entropy management
Skill configuration	Requires extra skill setup on the Agent platform	No extra skill configuration needed, works out of the box
Usage form	CLI + MCP + monitoring dashboard	Web UI + CLI, full-flow governance in natural language

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🚀 Quick Start

Install

curl -fsSL https://clawsomeflow.com/install.sh | bash

Common Commands

# Lifecycle
csflow start
csflow stop
csflow status
csflow doctor

# Flow / Run
csflow flows list
csflow runs list
csflow runs start <flow-id> --input k=v
csflow runs abort <run-id>

# Agent governance
csflow agents list
csflow agents create "Describe the Agent you want in natural language"
csflow agents chat <agent-id> "Keep improving this Agent's capabilities"

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👩‍💻 Contributor Local Deploy and Test

For contributors iterating on source code, use the isolated developer entrypoint:

bash scripts/deploy-contributor.sh

Default behavior of deploy-contributor.sh:

• Uses isolated data/runtime under ~/.clawsomeflow-dev (does not reuse ~/.clawsomeflow).
• Starts backend on 17117 and Vite on 5174.
• Keeps ClawTeam runtime isolated via ~/.clawsomeflow-dev/.clawteam-data.

bash scripts/deploy-contributor.sh is recommended for day-to-day source testing because it keeps regular user service state isolated.

Example with custom profile/ports:

CSFLOW_DEV_HOME=~/.clawsomeflow-dev-alice \
CSFLOW_DEV_BACKEND_PORT=18117 \
CSFLOW_DEV_FRONTEND_PORT=5184 \
bash scripts/deploy-contributor.sh

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🗺️ Roadmap

Phase	Content	Status
P0	Agent Store — a shareable marketplace for ready-made Agents, Teams and Flow templates: install, reuse, and contribute domain experts in one click.	🚧 In progress
P1	Broader Agent platform support — onboard more CLI Agent runtimes and keep pace with emerging ecosystems, so any Agent can join the same graph.	📅 Planned
P2	Mobile & server mode — a mobile-friendly console plus multi-user server deployment, to monitor and intervene in Runs anywhere.	💡 Exploring
P3	Cloud & SSH Agents — drive Agents on remote / cloud hosts over SSH, scaling collaboration beyond a single machine.	💡 Exploring

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🙏 Acknowledgements

• [ClawTeam] — the spark that inspired this project. Thank you for showing what Agent self-organization can be.
• Our Agent platform teammates — the real "team members" that do the actual work inside every Flow: Claude, OpenClaw, Codex, Gemini, and the growing roster of CLI Agents. ClawsomeFlow is only as clawsome as the Agents it coordinates.

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💬 WeChat Community

If ClawsomeFlow helps you coordinate your Agent team, please give us a ⭐ Star — it genuinely keeps us going.

Got questions about using ClawsomeFlow, or curious about building an OPC (One-Person Company)? Come hang out with us — scan the QR code below to join our WeChat discussion group:

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📄 License

MIT