Mirofish Offline Simulation

This is a fully local multi-agent simulation engine that generates hundreds of AI personas to predict how people will react to documents like press releases or policy drafts. It uses Neo4j for graph memory and Ollama for the LLM layer, so nothing hits cloud APIs. You feed it a document, it extracts entities and relationships, spawns agents with distinct personalities, then simulates them posting, arguing, and shifting opinions over simulated hours on platforms like Twitter or Reddit. The Python API is clean and the hybrid search combines vector similarity with BM25. Requires serious hardware though: the recommended qwen2.5:32b model needs 24GB VRAM, so you'll want to drop down to the 14b variant unless you have a beefy GPU.

skills.sh installs: 1.3K
GitHub stars: 61
last updated: Jul 14, 2026

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Install

$ npx -y skills add aradotso/trending-skills --skill mirofish-offline-simulation --agent claude-code

Installs into .claude/skills of the current project.

Files

MiroFish-Offline Skill

Skill by ara.so — Daily 2026 Skills collection.

MiroFish-Offline is a fully local multi-agent swarm intelligence engine. Feed it any document (press release, policy draft, financial report) and it generates hundreds of AI agents with unique personalities that simulate public reaction on social media — posts, arguments, opinion shifts — hour by hour. No cloud APIs required: Neo4j CE 5.15 handles graph memory, Ollama serves the LLMs.

Architecture Overview

Document Input
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Graph Build (NER + relationship extraction via Ollama LLM)
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Neo4j Knowledge Graph (entities, relations, embeddings via nomic-embed-text)
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Env Setup (generate hundreds of agent personas with personalities + memory)
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Simulation (agents post, reply, argue, shift opinions on simulated platforms)
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Report (ReportAgent interviews focus group, queries graph, generates analysis)
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Interaction (chat with any individual agent, full memory persists)

SKILL.md on GitHub

Details

Repository: github.com/aradotso/trending-skills
First seen: Apr 16, 2026