Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
Aoineco Squad Dispatch — Multi-Agent Task Router
Routes tasks to the best-suited agent based on skills, cost, availability, and priority, enabling parallel execution and load-balanced multi-agent orchestrat...
skill openclawclawhub Free
Routes tasks to the best-suited agent based on skills, cost, availability, and priority, enabling parallel execution and load-balanced multi-agent orchestrat...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/dispatch_engine.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- edmonddantesj
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Aoineco Squad Dispatch — Multi-Agent Task Router
Version: 1.0.0 Author: Aoineco & Co. License: MIT Tags: multi-agent, orchestration, dispatch, parallel, squad, task-routing
Description
Routes tasks to the right agent based on skills, availability, cost, and priority. Evolved from the dispatching-parallel-agents pattern into a full squad orchestration engine for multi-agent teams. Core principle: Right agent for right job. Cheapest agent for simple tasks. Best agent for critical tasks.
Problem
Multi-agent squads waste resources when: All tasks go to one expensive model Simple community posts use Claude Opus ($$$) instead of Gemini Flash ($) Tasks run sequentially when they could run in parallel No visibility into which agent costs what
Features
FeatureDescriptionSkill-Based RoutingMatches task requirements to agent specializationsCost-Aware DispatchPrefers cheaper agents for normal tasks, best agents for criticalDependency DetectionAutomatically groups parallel vs sequential tasksLoad BalancingRespects max concurrent tasks per agentNamed RosterPre-configured 7-agent squad with specializationsVisual PlansHuman-readable dispatch plans with cost estimates
Pre-Configured Squad
AgentSpecializationModelCost🧿 OracleGovernance, Strategyclaude-opus$$$⚔️ Blue-BladeSecurity, Auditclaude-sonnet$$📢 Blue-SoundCommunity, Contentgemini-flash$👁️ Blue-EyeResearch, Datagemini-flash$🧠 Blue-BrainStrategy, Analysisgemini-pro$$⚡ Blue-FlashBuild, Codeclaude-sonnet$$🗂️ Blue-RecordRecords, Docsgemini-flash$
Quick Start
from dispatch_engine import SquadDispatcher dispatcher = SquadDispatcher() dispatcher.add_task("Audit new skill", "Security scan", required_skills=["security"]) dispatcher.add_task("Post to BotMadang", "Korean content", required_skills=["community"]) dispatcher.add_task("Update docs", "Write summary", required_skills=["records"], depends_on=["TASK-0001", "TASK-0002"]) plan = dispatcher.plan() print(dispatcher.format_plan(plan))
File Structure
aoineco-squad-dispatch/ ├── SKILL.md # This file └── scripts/ └── dispatch_engine.py # Main engine (zero external dependencies)
Zero Dependencies
Pure Python 3.10+. No pip install needed. Designed for the $7 Bootstrap Protocol — every byte counts.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/dispatch_engine.py