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MiroFish — Swarm Intelligence Engine: upload seed data → simulate thousands of agents → predict future trajectories. GraphRAG + multi-agent simulation + interactive chat.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
SOC 職業分類に基づく
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/yanacuti1121/Yana-AI --skill 666ghj-mirofishコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
Sovereign-grade safety OS for AI coding agents. 62 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.
Use when the user wants to generate or keep repository documentation up to date via OpenWiki (langchain-ai/openwiki) — an LLM-driven CLI that writes a wiki for a codebase (or a personal knowledge base from Notion/Gmail/Slack/X/web search) and keeps it fresh via a scheduled CI pull request. Examples: "set up OpenWiki for this repo", "keep the docs updated automatically", "generate an agent wiki".
Use when implementing the core AR pipeline (camera pose estimation, marker tracking, projection overlay) from first principles — not when just using ARKit/ARCore/Unity's AR framework as a black box. Triggers on: 'build augmented reality from scratch', 'marker-based AR tracking', 'camera pose estimation', 'implement fiducial marker detection', 'AR projection matrix math', 'markerless AR tracking'. Covers marker-based vs markerless tracking, pose estimation, and the projection math to overlay 3D content on a camera feed.
| name | 666ghj--mirofish |
| description | MiroFish — Swarm Intelligence Engine: upload seed data → simulate thousands of agents → predict future trajectories. GraphRAG + multi-agent simulation + interactive chat. |
| allowed-tools | Bash, Read, Write |
| user-invocable | true |
MiroFish: prediction engine dùng multi-agent swarm — build digital simulation từ seed data, run thousands of agents interact và evolve, dự đoán future trajectories.
Stage 1 — Graph Building
Ingest seed data (reports, news, stories)
Build GraphRAG structures + memory injection
Stage 2 — Environment Setup
Extract entity relationships
Generate agent personas
Configure interaction rules
Stage 3 — Simulation
Run parallel dual-platform simulations
Dynamic temporal memory updates
Thousands of agents interact + evolve
Stage 4 — Report Generation
ReportAgent với specialized toolsets
Post-simulation analysis + insights
Stage 5 — Deep Interaction
Chat với simulated agents
Chat với ReportAgent về findings
Frontend: Node.js 18+ (localhost:3000)
Backend: Python 3.11-3.12 (localhost:5001)
LLM: Alibaba Qwen (recommended) hoặc bất kỳ OpenAI-compatible
Memory: Zep Cloud
Deploy: source code hoặc Docker
git clone https://github.com/666ghj/MiroFish
cd MiroFish
# Setup .env với LLM API key
docker-compose up
# Frontend: localhost:3000
# Upload seed data → describe prediction → get report
https://github.com/666ghj/MiroFish · MIT · +493⭐/day