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EvoAgentX Workflow

Bridge EvoAgentX (1000+ star open-source framework) with OpenClaw. Enables self-evolving agentic workflows - workflows that automatically improve over time t...

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Bridge EvoAgentX (1000+ star open-source framework) with OpenClaw. Enables self-evolving agentic workflows - workflows that automatically improve over time t...

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, scripts/evoagentx_cli.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.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. 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

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.2

Documentation

ClawHub primary doc Primary doc: SKILL.md 14 sections Open source page

EvoAgentX Workflow Integration

Integrates the EvoAgentX framework with OpenClaw for self-evolving agentic workflows.

When to Use This Skill

Use this skill when: Building multi-agent workflows that need to evolve over time Evaluating and optimizing existing agent workflows Implementing the Genome Evolution Protocol (GEP) Creating self-improving agent systems Migrating static workflows to self-evolving ones

CLI Usage

This skill provides a command-line interface for EvoAgentX operations: # Check if EvoAgentX is installed python3 scripts/evoagentx_cli.py status # Get installation instructions python3 scripts/evoagentx_cli.py install # Show usage examples python3 scripts/evoagentx_cli.py examples # Create a workflow template python3 scripts/evoagentx_cli.py create-workflow \ --name ResearchWorkflow \ --description "A research automation workflow" # Check EvoAgentX status python3 scripts/evoagentx_cli.py check

Installation

# Install EvoAgentX framework pip install evoagentx # Verify installation python3 -c "import evoagentx; print(evoagentx.__version__)"

1. Create a Basic Workflow

After running create-workflow, edit the generated Python file: from evoagentx import Agent, Workflow class MyWorkflow(Workflow): async def execute(self, context): # Your workflow logic here result = await self.run_agents(context) return result

2. Enable Self-Evolution

from evoagentx.evolution import EvolutionEngine engine = EvolutionEngine() optimized_workflow = await engine.evolve( workflow=MyWorkflow(), iterations=10, evaluation_criteria={"accuracy": 0.95} )

Workflows

Multi-agent orchestration State management Tool integration

Evolution Strategies

TextGrad: Prompt optimization AFlow: Workflow structure optimization MIPRO: Multi-step reasoning optimization

Genomes

Encoded success patterns containing: Task type classification Approach methodology Outcome metrics Context requirements

Pattern 1: Research Workflow Evolution

# Start with basic research workflow workflow = ResearchWorkflow() # Evolve for better results evolution = await workflow.evolve( dataset=research_queries, metric="comprehensiveness" )

Pattern 2: Tool Selection Optimization

# EvoAgentX automatically selects optimal tools workflow = AgentWorkflow( tools=["web_search", "browser", "file_io"], auto_select=True )

Security Considerations

All evolution happens locally (no data exfiltration) Genomes contain no credentials Evaluation uses synthetic data when possible

References

EvoAgentX GitHub: https://github.com/EvoAgentX/EvoAgentX Documentation: https://evoagentx.github.io/EvoAgentX/ arXiv Paper: https://arxiv.org/abs/2507.03616

Version

1.0.0 - Initial release with core EvoAgentX integration

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 Primary doc
  • scripts/evoagentx_cli.py Scripts