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gl813788-byte

Agent Weave

by gl813788-byte · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install agent-weave
Description
Master-Worker Agent Cluster for parallel task execution. Use when building distributed agent systems with parallel processing needs, task orchestration, or M...
README (SKILL.md)

Agent-Weave

Master-Worker Agent Cluster with parallel task execution and secure parent-child communication.

When to Use This Skill

Use agent-weave when you need to:

  • Build distributed agent systems with parallel processing
  • Orchestrate multiple agents working together
  • Implement MapReduce-style workflows
  • Scale task execution across worker agents
  • Build master-worker architectures

Quick Start

Installation

npm install agent-weave

Basic Usage

const { Loom } = require('agent-weave');

// Create cluster
const loom = new Loom();
const master = loom.createMaster('my-cluster');

// Create workers
const workers = loom.spawnWorkers(master.id, 5, async (data) => {
  // Process data
  return { result: data * 2 };
});

// Execute tasks
const results = await master.dispatch([1, 2, 3, 4, 5]);
console.log(results);

CLI Commands

# Create master
weave loom create-master --name my-cluster

# Spawn workers
weave loom spawn --parent \x3Cmaster-id> --count 5

# List agents
weave loom list --tree

Features

  • Master-Worker Architecture: Orchestrate multiple worker agents
  • Parallel Execution: Distribute tasks across workers
  • Secure Communication: Parent-child relationship enforcement
  • MapReduce Support: Built-in map-reduce workflows
  • Auto-scaling: Dynamic worker management
  • Event-driven: EventEmitter-based communication

API Reference

Loom

Factory for creating and managing agents.

Master

Manages a cluster of worker agents.

Worker

Executes tasks assigned by the master.

Thread

Secure communication layer between agents.

Tapestry

Task orchestration engine for MapReduce workflows.

License

MIT

Usage Guidance
This package appears to implement the master/worker features it advertises, but there are multiple quality and runtime concerns you should consider before installing or running it: - Packaging bugs: package.json's 'bin' claims a 'bin/weave' entry that is missing; the included test report documents CLI entry-point issues. Prefer not to npm install -g this globally until the maintainer fixes the bin entry. - File writes: the library and demos write logs and agent state to disk (default ./agent-logs). If you run it, set logDir to a controlled location and avoid running as a privileged user. - Long-running agents: AGENT_SYSTEM.md and code allow child agents with timeout: 0 (no timeout) and use setInterval heartbeats. That can create long-running processes and resource leaks; run inside a container or VM and enforce resource/time limits. - Code quality bugs: duplicate method definitions, missing imports (some demo files use fs without requiring it), and duplicated/overridden getters are present. These look like sloppy packaging rather than intentional malice, but they could cause unexpected behavior. - No network exfiltration found: there are no obvious outbound network calls, credential requests, or hidden endpoints in the provided files. Recommendations: 1) Review the code (lib/ and agent-system files) locally before running. 2) Run in an isolated environment (container or sandbox) and avoid global install. 3) Configure logDir and limits, and prefer programmatic use in controlled tests before using in production. 4) If you need CLI functionality, wait for the maintainer to fix the bin packaging or inspect/adjust bin/weave.mjs / bin/weave-cli-safe.js before use. Given the packaging and runtime surprises, treat this as potentially risky until you validate and sandbox it.
Capability Analysis
Type: OpenClaw Skill Name: agent-weave Version: 1.0.0 The OpenClaw AgentSkills skill bundle 'agent-weave' appears benign. It implements a Master-Worker agent cluster for parallel task execution, with local file system operations (`fs.writeFileSync`, `fs.appendFileSync`, `fs.mkdirSync` in `agent-system.js`) used legitimately for logging and managing agent state within a configurable local directory (`./agent-logs`). The `lib/thread.js` module provides an internal, secure communication layer between agents within the cluster, not for external network connections. There is no evidence of data exfiltration, unauthorized command execution (e.g., `child_process`, `eval` of untrusted input), persistence mechanisms, or prompt injection attempts in any of the markdown files. Identified issues in `TEST_REPORT.md` relate to CLI functionality and code quality, not security vulnerabilities or malicious intent.
Capability Assessment
Purpose & Capability
Name/description align with the code: Loom/Master/Worker classes, MapReduce demo, CLI helpers and examples. The code does not request unrelated cloud credentials or network endpoints.
Instruction Scope
SKILL.md and examples describe npm install and CLI usage but do not call out that runtime will create local log/state files (./agent-logs) and spawn long-running agents with no timeout (AGENT_SYSTEM.md explicitly documents 'timeout: 0'). The runtime docs/examples also include long-lived setInterval heartbeats and file writes; these are outside what a casual user might expect from a small orchestration library.
Install Mechanism
No install spec is provided to the platform (instruction-only), but the skill bundle contains a complete Node package (package.json, lib/, bin/, examples). The package.json 'bin' points to a missing file ('bin/weave'), and the test report documents CLI entry issues — this is a packaging bug rather than an obvious supply-chain red flag. No external downloads or obscure URLs are used.
Credentials
The skill requests no environment variables or credentials. It does perform local file I/O (logs and saved agent state under a configurable logDir) which is proportionate to an agent manager, but users should be aware files are written into working directories by default.
Persistence & Privilege
Skill does not request always:true or elevated platform privileges and does not modify other skills. However, code runs long-lived timers and can spawn many workers/tasks (examples spawn 100 workers and dispatch 1000 tasks) which could consume host resources if the skill is invoked autonomously — consider sandboxing or resource limits.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agent-weave
  3. After installation, invoke the skill by name or use /agent-weave
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of agent-weave: - Provides a Master-Worker Agent Cluster for parallel task execution and secure agent communication. - Supports distributed agent systems, scalable orchestration, and MapReduce-style workflows. - Includes API for Loom, Master, Worker, Thread, and Tapestry components. - Offers CLI commands for managing clusters, spawning workers, and listing agents. - Features event-driven communication and auto-scaling of worker agents.
Metadata
Slug agent-weave
Version 1.0.0
License
All-time Installs 2
Active Installs 2
Total Versions 1
Frequently Asked Questions

What is Agent Weave?

Master-Worker Agent Cluster for parallel task execution. Use when building distributed agent systems with parallel processing needs, task orchestration, or M... It is an AI Agent Skill for Claude Code / OpenClaw, with 795 downloads so far.

How do I install Agent Weave?

Run "/install agent-weave" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent Weave free?

Yes, Agent Weave is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Agent Weave support?

Agent Weave is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent Weave?

It is built and maintained by gl813788-byte (@gl813788-byte); the current version is v1.0.0.

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