clawsomeflow 0.1.21b9

Vertical agent workflow orchestration platform on top of ClawTeam and OpenClaw

🌐 clawsomeflow.com · 📖 Docs

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Turn your goal into a task flow, and let an active scheduler drive a team of AI agents to execute it — parallel, isolated, observable, and convergent. You orchestrate the work; ClawsomeFlow keeps it under control.

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

Quick Start · Docs · News · Who Should Try It · Core Features · How It Works · Why ClawsomeFlow · Contributor Local Deploy · Roadmap · WeChat Community

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📰 News

• 2026-06-02: ClawsomeFlow public release 🎉

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🎯 Who Should Try It?

• Building a software engineering agent team that can develop in parallel across local branches;
• Developers and teams who need multiple agents to collaborate like a real team (plan, implement, verify, converge) — not just more chat windows;
• Founders and operators building an AI-native company, delegating repeatable work to orchestrated agent teams;
• Ambitious super-individual creators — one person steering many specialized agents to continuously amplify output;
• Engineering-minded folks done with prompt-only black-box orchestration — predictable behavior, controllable cost, rollback guardrails.

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✨ Core Features

ClawsomeFlow turns scattered AI agents into a controllable engineering system — from the first instruction to the final, reviewable result.

🗣️ Get it done in natural language	🧠 Precise orchestration, not guesswork	🚀 Many agents, one graph
Define flows, create agents, orchestrate tasks, and step in at runtime — all by describing what you want. No glue code, no SDK wrangling.	Control flow lives in code, not in a prompt. The scheduler decides dispatch, retry, timeout and convergence — so behavior is predictable and tokens aren't wasted.	Lay out your work as a DAG and let multiple agents collaborate in parallel; a leader summarizes and converges the results into one deliverable.

🔐 Isolation & rollback by default	📊 Observability you can audit	🔄 A system that improves itself
Built on Git worktree isolation with a built-in cross-process repo lock, ensuring absolute reliability of all agent collaboration behaviors; supports intelligent merge and rollback, plus optional human checkpoints for in-flight course correction.	Every dispatch, completion and failure is recorded as a RunEvent — each run is traceable, replayable and reviewable, with no black boxes.	Not happy with a result? File a complaint and the system reflects, reworks, and writes the lesson back — so the next run is better than the last.

ClawsomeFlow inherits the following capabilities from ClawTeam:

• Git Worktree parallel isolation foundation: each Agent has an independent branch and directory, naturally fitting multi-agent parallel development.
• Inter-Agent messaging: point-to-point inbox and broadcast, so team members share progress in real time.

On top of this, ClawsomeFlow adds AI combined with precise orchestration, enhanced Harness engineering (built-in cross-process repo lock for absolutely reliable multi-branch parallel development, intelligent merge and rollback, complaint-loop mechanism, optional human checkpoints for in-flight correction), deep OpenClaw/Hermes adaptation, and Web productization.

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🛠️ How It Works

From a sentence to a shipped result. You stay in charge of the goal; ClawsomeFlow handles the coordination, the parallelism, and the recovery when things go wrong.

1. Describe your goal — Tell ClawsomeFlow what you want in plain language, or compose a Flow visually as a graph of tasks and dependencies.
2. Agents run in parallel — The scheduler actively dispatches ready tasks to the right agents, each in its own isolated workspace, and drives them to completion.
3. Watch, steer, recover — Follow every step live. Retry, skip or abort with clear strategies, and approve results at human checkpoints before anything lands.
4. Converge & deliver — A leader merges the parallel work into one reviewed deliverable — and the run history stays fully auditable.

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🧪 Developer Mode

Developer mode offers software-development collaboration projects a more flexible way to collaborate.

• Upstream context for every subtask: for each direct dependency, a subtask is injected with the upstream agent id, worktree path, branch and base branch, so it can flexibly build on that work — inspect it, merge that branch, or raise a PR for it — driven entirely by your task description.
• Cross-branch collaboration in plain language: in a downstream task, just write "merge upstream agent X's worktree branch into branch Y" or "open a PR for X".
• Built-in lock = absolute parallel-merge reliability: many branches can develop and merge in parallel without ever racing or corrupting the repo. Whether the scheduler or an agent merges, every merge is serialized on the same lock — you can even direct cross-branch merges or PRs in plain language without risk.
• Per-subtask auto-merge control: each subtask can independently toggle auto-merge into the baseline branch.
• Unique worktree per agent: each agent creates its own worktree and independent branch from the baseline branch.
• PR-friendly flow: for subtasks you want to land via PR or manual review, turn auto-merge OFF.

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🤖 Supported Agents

Agent	Kind	Runtime	Status
OpenClaw	openclaw	TUI	⭐ Deeply adapted
Hermes	hermes	TUI	⭐ Deeply adapted
Claude Code	claude	TUI	✅ Full support
Codex	codex	TUI	✅ Full support
Cursor	cursor	TUI	✅ Full support
OpenCode	opencode	TUI	Testing
Gemini CLI	gemini	TUI	Testing
Kimi CLI	kimi	TUI	Testing
Qwen Code	qwen	TUI	Testing
Qoder CLI	qoder	TUI	Testing
CodeBuddy Code	codebuddy	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; a built-in cross-process repo lock makes parallel multi-branch development and merging absolutely reliable
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
Parallel-merge reliability	No repo-level merge lock — concurrent baseline merges race and can corrupt git metadata; completely uncontrolled	Built-in cross-process repo lock guarantees the absolute reliability of parallel multi-branch development
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

Before you start — make sure your agent CLIs work. ClawsomeFlow drives external agent CLIs (claude, codex, hermes, …) and agents inherit your global CLI authentication. So first install and log in to each CLI you plan to use and confirm it runs on its own (e.g. claude -p hi, hermes chat, codex). If a CLI isn't authenticated, agents using it will stall on a login prompt. For Hermes you can also set the model/provider/key per agent in Settings → Model. If you hit auth errors, verify the CLI's own model/provider config first.

Qoder / CodeBuddy need a one-time auth: CodeBuddy via codebuddy → interactive login; Qoder via export QODER_PERSONAL_ACCESS_TOKEN=… (or qodercli → /login). ClawsomeFlow auto-seeds their folder-trust config (trustAll / trustDirectories) so unattended runs don't stall on the "trust this folder?" prompt — no action needed there.

Install

Linux/macOS

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

Common Commands

Most of the time you only need these three:

csflow start      # start the service, print the console URL
csflow status     # is it running? version, mode, paths
csflow upgrade    # update to the latest release (flows/runs/settings preserved)

A few more for day-to-day use:

# Lifecycle
csflow stop
csflow doctor                              # health check (deps + config + gateway)
csflow uninstall --yes                     # stop service + unregister OpenClaw (keep data)
csflow uninstall --purge-data              # full wipe: type PURGE to confirm (irreversible)

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

# Agent governance
csflow agents list
# Creating agents and chatting with them is done in the Web UI ("My Team"),
# not the CLI.

Every command accepts --help. Full CLI reference: https://clawsomeflow.com/docs/

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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

Stop the contributor service

To stop the contributor profile started by deploy-contributor.sh, use the dedicated stop script:

bash scripts/stop-contributor.sh

Do not use csflow stop for the contributor profile — that targets the end-user service. If you used a custom profile, pass the same env overrides:

CSFLOW_DEV_BACKEND_PORT=18117 CSFLOW_DEV_FRONTEND_PORT=5184 \
bash scripts/stop-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.	🚧 In progress
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