slime-strategy

Set up a slime-mold inspired parallel autonomy workflow for AI agent exploration.

3|1|Updated Dec 12, 2025

Search Tags:#workflow-automation #branch-management #iteration-tracking #genetic-algorithm #slime-mold #parallel-autonomy

Ready to run

npx skills add https://github.com/tilmon-engineering/claude-skills --skill slime-strategy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: slime-strategy
Source: https://github.com/tilmon-engineering/claude-skills/tree/main/plugins/autonomy/skills/slime-strategy
Command: npx skills add https://github.com/tilmon-engineering/claude-skills --skill slime-strategy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables you to quickly set up and manage a slime-mold–inspired parallel-autonomy workflow, coordinating multiple exploration branches to cooperate and amplify problem-space coverage.

Core Features & Use Cases

Parallel exploration: Launch multiple autonomy branches that explore different approaches to the same goal and share learnings.
Cooperative feedback: Use cross-pollination to integrate insights from successful branches into others, improving overall discovery.
Lifecycle governance: Create and maintain goals, documentation, and iteration tracking for autonomous experiments.

Quick Start

Run the slime command to initialize the slime mold strategy and parallel branches for the current problem.

Frequently Asked Questions about slime-strategy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is a slime-mold inspired parallel autonomy workflow for AI agents?▼

A slime-mold inspired parallel autonomy workflow coordinates multiple concurrent AI agent branches to explore a problem space. These branches exchange insights through cross-pollination and converge on effective solutions, amplifying overall discovery coverage.

How do I set up parallel exploration branches for concurrent AI agent workflows?▼

Run the slime command to initialize the parallel autonomy workflow. This creates governance documentation, initial branch structures, and iteration tracking to manage concurrent exploration branches sharing learnings.

How does iteration tracking work for parallel autonomous experiments?▼

Iteration tracking uses an iteration-0000 baseline and commands like /fork-iteration, /analyze-branch, and /start-iteration to govern autonomous experiments. This lifecycle governance maintains goals and monitors branch progress.

Can I use cross-pollination to share insights between different exploration branches?▼

Yes, cross-pollination integrates insights from successful branches into others. This cooperative feedback mechanism allows parallel exploration branches to share learnings and improve overall problem-space discovery.

What's the best way to govern multiple concurrent AI agent branches exploring the same goal?▼

Use autonomy governance documentation to manage concurrent AI agent branches. Establish initial branch structures and apply iteration tracking commands to coordinate multiple approaches exploring the same goal.

Do I need specific dependencies to run a genetic algorithm workflow for branch management?▼

No specific dependencies are required to run the branch management workflow. The system relies on internal commands and documentation structures to implement genetic algorithm inspired parallel autonomy.