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swarm-executor
by
xb19960921
· GitHub ↗
· v1.1.0
· MIT-0
94
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2
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Install in OpenClaw
/install swarm-executor
Description
Coordinate multi-agent swarm execution with a lightweight Pub/Sub protocol, standardized SwarmCommand messages, token-budget control, agent status tracking,...
Usage Guidance
This skill appears to do what it claims: a library for coordinating multi-agent workflows with in-memory or Redis Pub/Sub, token budgeting, negotiation, and agent tracking. Before installing or running it:
- If you plan to use Redis, provide a trusted redis_url only (do not point to unknown/public Redis servers). Messages published to Redis can contain task payloads and could be read by whoever controls that Redis instance.
- The registry package includes requirements.txt (fastapi, uvicorn, python-dotenv, etc.). Because there is no install spec, those dependencies won't be auto-installed — install only the packages you need. The full stack (FastAPI/uvicorn) may pull in a webserver surface you should review.
- SKILL.md examples contain a minor API mismatch (use_redis=True vs the actual PubSubCoordinator signature). Double-check examples against the code before copying.
- The code sets up default agent IDs and includes logic where agent "001" (CEO) can cancel negotiations; if you map external agents to those IDs, ensure authentication/authorization is enforced by your deployment to prevent unauthorized cancellations.
- Review docker-compose.yml and any omitted files before running to ensure they don't start unexpected network services.
If you need a second opinion, provide the docker-compose.yml and any omitted runtime files and I can check them for external endpoints or secret handling.
Capability Analysis
Type: OpenClaw Skill
Name: swarm-executor
Version: 1.1.0
The swarm-executor bundle is a well-structured framework for multi-agent orchestration and task coordination. It implements a standardized communication protocol (SwarmCommand), state management, and token-budgeting logic using Redis or in-memory Pub/Sub. The SKILL.md instructions emphasize safety, explicitly directing the agent to seek human confirmation for destructive or costly actions, and the Python code (e.g., swarm_protocol.py, pubsub.py) contains no evidence of malicious execution, data exfiltration, or obfuscation.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description (swarm coordination, Pub/Sub, token budgeting, negotiation) align with the included modules (swarm_protocol, pubsub, token_budget, agent_manager, negotiation). The code implements the advertised features and default agent IDs/roles that the SKILL.md references.
Instruction Scope
SKILL.md stays on-topic (create/validate/publish SwarmCommand, track state, enforce budgets). Minor inconsistency: SKILL.md example uses PubSubCoordinator(use_redis=True) while the code's PubSubCoordinator constructor expects a backend enum and optional redis_url; the README-driven example won't work without adjusting parameters. The runtime instructions do not tell the agent to read arbitrary host files or to exfiltrate secrets, but published messages can go to a user-supplied Redis instance (see guidance).
Install Mechanism
No install spec in registry (instruction-only), but the repo includes requirements.txt listing redis, pydantic, fastapi, uvicorn, python-dotenv, etc. Because there's no automatic installer, these dependencies will not be installed by the platform — a manual install may be needed. The listed packages are plausible for optional Redis and an HTTP API, but they are heavier than the core library needs if you only use the in-memory backend.
Credentials
The skill declares no required environment variables or primary credentials. The code supports connecting to Redis via a redis_url parameter (not an env var), which is proportional to the described Redis-backed Pub/Sub feature. No unrelated cloud credentials or secrets are requested by the package.
Persistence & Privilege
always is false and the package does not request elevated platform privileges. It defines module-level singletons (a global coordinator) but does not attempt to modify other skills or global agent configuration. Autonomous invocation is allowed by default (normal) but no extra permanent presence is requested.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install swarm-executor - After installation, invoke the skill by name or use
/swarm-executor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
**Changelog for swarm-executor v1.1.0**
- Skill rebranded to "swarm-coordinator", public wording generalized.
- Introduced modular coordinator architecture: agent management, negotiation, token budget, and swarm protocol modules.
- Shifted from file/batch parallelization to a protocol-driven swarm command workflow (standardized commands, status schemas, ownership, and boundaries).
- Added Redis/in-memory Pub/Sub support for multi-agent orchestration.
- New safety controls: token-budget governance, negotiation rules, failure handling, fallback, and completion-state validation.
- Includes validation checklists, execution workflow guide, and a test suite for coordination primitives.
v1.0.0
Initial release of the parallel-task-executor skill:
- Automates splitting of large tasks into manageable sub-tasks with ≤5 minutes per batch.
- Spawns multiple sub-agents for true parallel execution, with real-time progress monitoring and timeout handling.
- Supports automatic progress saving and recovery (断点续传) for interrupted or failed executions.
- Aggregates results and provides detailed reports on execution efficiency and outcomes.
- Includes dynamic parameter adjustment and robust error handling for retries and user notification.
- Proven to boost efficiency by 3–6x in practical scenarios (e.g., mass PDF analysis, knowledge base health checks).
Metadata
Frequently Asked Questions
What is swarm-executor?
Coordinate multi-agent swarm execution with a lightweight Pub/Sub protocol, standardized SwarmCommand messages, token-budget control, agent status tracking,... It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.
How do I install swarm-executor?
Run "/install swarm-executor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is swarm-executor free?
Yes, swarm-executor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does swarm-executor support?
swarm-executor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created swarm-executor?
It is built and maintained by xb19960921 (@xb19960921); the current version is v1.1.0.
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