Agent skill · software engineering · aradotso
mirofish-offline-simulation
Fully local multi-agent swarm intelligence simulation engine using Neo4j + Ollama for public opinion, market sentiment, and social dynamics prediction.
Why this skill is useful
Adds executable scripts for setting up a local multi-agent simulation environment with Neo4j and Ollama, which the AI cannot generate from existing knowledge.
What it needs
Requires docker, ollama installed locally. About 7k tokens when loaded. Last updated 2026-07-09. 70 stars on the source repository.
What this skill does
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 Backend: Flask + Python 3.11 Frontend: Vue 3 + Node 18 Graph DB: Neo4j CE 5.15 (bolt protocol) LLM: Ollama (OpenAI-compatible /v1 endpoint) Embeddings: nomic-embed-text (768-dimensional, via Ollama) Search: Hybrid — 0.7 × vector similarity + 0.3 × BM25 --- Installation Option A: Docker (Recommended) Open http://localhost:3000. Option B: Manual Setup 1. Neo4j 2. Ollama 3. Backend 4. Frontend --- Configuration (.env) --- Core Python API GraphStorage Interface The abstraction layer between MiroFish and the graph database: Building a Knowledge Graph from a Document Creating and Running a Simulation Querying Simulation Results Chatting with a Simulated Agent Hybrid Search on the Knowledge Graph Implementing a Custom GraphStorage Backend Flask App Integration Pattern Accessing Storage in a Flask Route --- REST API Reference Method Endpoint Description -------- ---------- ------------- POST /api/graph/build Upload document, build knowledge graph GET /api/graph/:id Get graph entities and relationships POST /api/simulation/create Create simulation environment POST /api/simulation/run Execute simulation GET /api/simulation/:id/results Get posts, sentiment, metrics GET /api/simulation/:id/agents List generated agents POST /api/report/generate Generate ReportAgent analysis POST /api/agent/:id/chat Chat with a specific agent GET /api/search Hybrid search the knowledge graph Example: Build graph from document Example: Run a simulation --- Hardware Selection Guide Use Case Model VRAM RAM ---------- ------ …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/mirofish-offline-simulation