From aradotso-trending-skills-37
Build and configure personal AI agents in OpenHanako Electron app with persistent memory, personalities, autonomy for files, terminal, web, JS execution, and multi-agent collaboration.
npx claudepluginhub joshuarweaver/cascade-ai-ml-agents-misc-1 --plugin aradotso-trending-skills-37This skill uses the workspace's default tool permissions.
> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Generates original PNG/PDF visual art via design philosophy manifestos for posters, graphics, and static designs on user request.
Skill by ara.so — Daily 2026 Skills collection.
OpenHanako is a desktop AI agent platform built on Electron that gives each agent persistent memory, a distinct personality, and the ability to autonomously operate your computer — read/write files, run terminal commands, browse the web, execute JavaScript, and manage schedules. Multiple agents can collaborate via channel group chats or task delegation.
# macOS Apple Silicon — download from releases page
# https://github.com/liliMozi/openhanako/releases
# Mount the .dmg and drag to Applications
# First launch — bypass Gatekeeper (one-time):
# Right-click app → Open → Open
# Windows — run the .exe installer from releases
# SmartScreen warning: click "More info" → "Run anyway"
git clone https://github.com/liliMozi/openhanako.git
cd openhanako
npm install
# Development mode
npm run dev
# Build for production
npm run build
# Run tests
npm test
On first launch, the wizard asks for:
chat model — main conversation (e.g. gpt-4o, deepseek-chat)utility model — lightweight tasks, summarization (e.g. gpt-4o-mini)utility large model — memory compilation, deep analysis (e.g. gpt-4o)// OpenAI
{
"baseURL": "https://api.openai.com/v1",
"apiKey": "process.env.OPENAI_API_KEY"
}
// DeepSeek
{
"baseURL": "https://api.deepseek.com/v1",
"apiKey": "process.env.DEEPSEEK_API_KEY"
}
// Local Ollama
{
"baseURL": "http://localhost:11434/v1",
"apiKey": "ollama"
}
// Qwen (Alibaba Cloud)
{
"baseURL": "https://dashscope.aliyuncs.com/compatible-mode/v1",
"apiKey": "process.env.DASHSCOPE_API_KEY"
}
openhanako/
├── core/ # Engine orchestration + Managers (Agent, Session, Model, Preferences, Skill)
├── lib/ # Core libraries
│ ├── memory/ # Custom memory system (recency decay)
│ ├── tools/ # Built-in tools (files, terminal, browser, screenshot, canvas)
│ ├── sandbox/ # PathGuard + OS-level isolation (Seatbelt/Bubblewrap)
│ └── bridge/ # Multi-platform adapters (Telegram, Feishu, QQ)
├── server/ # Fastify 5 HTTP + WebSocket server
├── hub/ # Scheduler, ChannelRouter, EventBus
├── desktop/ # Electron 38 main process + React 19 frontend
├── tests/ # Vitest test suite
└── skills2set/ # Built-in skill definitions
| Manager | Responsibility |
|---|---|
AgentManager | Create, load, delete agents |
SessionManager | Conversation sessions per agent |
ModelManager | Route requests to configured providers |
PreferencesManager | User/global settings |
SkillManager | Install, enable, disable, sandbox skills |
Each agent is a self-contained folder you can back up:
~/.openhanako/agents/<agent-id>/
├── personality.md # Personality template (free-form prose or structured)
├── memory/
│ ├── working.db # Recent events (SQLite WAL)
│ └── compiled.md # Long-term compiled memory
├── desk/ # Agent's file workspace
│ └── notes/ # Jian notes
└── skills/ # Agent-local installed skills
# Hanako
You are Hanako, a calm and thoughtful assistant who prefers directness over verbosity.
You remember past conversations and refer to them naturally.
You ask clarifying questions before starting large tasks.
When writing code, you always add brief inline comments.
## Tone
- Warm but professional
- Uses occasional dry humor
- Never uses hollow affirmations ("Great question!")
## Constraints
- Always confirm before deleting files
- Summarize long terminal output rather than dumping it raw
Skills extend agent capabilities. They live in skills2set/ (built-in) or are installed per-agent.
// Via the Skills UI in the app, or programmatically:
const { skillManager } = engine;
await skillManager.installFromGitHub({
repo: 'some-user/hanako-skill-weather',
agentId: 'agent-abc123',
safetyReview: true // strict review enabled by default
});
---
name: web-scraper
version: 1.0.0
description: Scrape structured data from web pages
tools:
- browser
- javascript
permissions:
- network
---
## Instructions for Agent
When asked to scrape a page:
1. Use the `browser` tool to navigate to the URL
2. Use `executeJavaScript` to extract structured data
3. Save results to the desk as JSON
// skills/my-skill/index.js
export default {
name: 'my-skill',
version: '1.0.0',
description: 'Does something useful',
// Tools this skill adds to the agent
tools: [
{
name: 'fetch_weather',
description: 'Fetch current weather for a city',
parameters: {
type: 'object',
properties: {
city: { type: 'string', description: 'City name' }
},
required: ['city']
},
async execute({ city }) {
const res = await fetch(
`https://wttr.in/${encodeURIComponent(city)}?format=j1`
);
const data = await res.json();
return {
temp_c: data.current_condition[0].temp_C,
description: data.current_condition[0].weatherDesc[0].value
};
}
}
]
};
OpenHanako uses a recency-decay memory model: recent events stay sharp, older ones fade.
// Accessing memory programmatically (core/lib/memory)
import { MemoryManager } from './lib/memory/index.js';
const memory = new MemoryManager({ agentId: 'agent-abc123' });
// Store a memory event
await memory.store({
type: 'conversation',
content: 'User prefers dark mode and terse responses',
importance: 0.8 // 0.0–1.0; higher = decays slower
});
// Retrieve relevant memories
const relevant = await memory.query({
query: 'user preferences',
limit: 10,
minRelevance: 0.5
});
// Trigger manual compilation (normally runs automatically)
await memory.compile();
| Tier | Storage | Decay |
|---|---|---|
| Working memory | working.db (SQLite) | Fast — recent N turns |
| Compiled memory | compiled.md | Slow — summarized by utility-large model |
| Desk notes (Jian) | Files on desk | Manual / no decay |
Tools available to agents out of the box:
// File operations
{ tool: 'read_file', args: { path: '/Users/me/notes.txt' } }
{ tool: 'write_file', args: { path: '/Users/me/out.txt', content: '...' } }
// Terminal
{ tool: 'run_command', args: { command: 'ls -la', cwd: '/Users/me' } }
// Browser & web
{ tool: 'browse', args: { url: 'https://example.com' } }
{ tool: 'web_search', args: { query: 'OpenHanako latest release' } }
// Screen
{ tool: 'screenshot', args: {} }
// Canvas
{ tool: 'draw', args: { instructions: '...' } }
// Code execution
{ tool: 'execute_js', args: { code: 'return 2 + 2' } }
Tier 0 — Denied: System paths (/System, /usr, registry hives)
Tier 1 — Read-only: Home directory files outside agent desk
Tier 2 — Read-write: Agent desk folder only
Tier 3 — Full: Explicitly granted paths (user confirms)
OS-level sandbox: macOS Seatbelt / Linux Bubblewrap wraps the skill process.
// core/AgentManager usage example
import { createEngine } from './core/engine.js';
const engine = await createEngine();
// Create a second agent
const researchAgent = await engine.agentManager.create({
name: 'Researcher',
personalityTemplate: 'researcher.md',
models: {
chat: 'deepseek-chat',
utility: 'gpt-4o-mini',
utilityLarge: 'gpt-4o'
}
});
// Delegate a task from one agent to another via channel
await engine.hub.channelRouter.delegate({
fromAgent: 'agent-abc123',
toAgent: researchAgent.id,
task: 'Find the top 5 papers on mixture-of-experts published in 2025',
returnTo: 'agent-abc123' // result routed back automatically
});
// hub/scheduler usage
import { Scheduler } from './hub/scheduler.js';
const scheduler = new Scheduler({ agentId: 'agent-abc123' });
// Run a task every day at 9am
scheduler.cron('daily-briefing', '0 9 * * *', async () => {
await agent.run('Summarize my desk notes from yesterday and post to #briefing channel');
});
// Heartbeat — check desk for new files every 5 minutes
scheduler.heartbeat('desk-watch', 300_000, async () => {
const changed = await agent.desk.checkChanges();
if (changed.length > 0) {
await agent.run(`New files on desk: ${changed.join(', ')} — summarize and notify me`);
}
});
scheduler.start();
Connect one agent to Telegram, Feishu, and QQ simultaneously:
// lib/bridge configuration
const bridgeConfig = {
telegram: {
enabled: true,
token: process.env.TELEGRAM_BOT_TOKEN,
allowedUsers: [process.env.TELEGRAM_ALLOWED_USER_ID]
},
feishu: {
enabled: true,
appId: process.env.FEISHU_APP_ID,
appSecret: process.env.FEISHU_APP_SECRET
},
qq: {
enabled: false
}
};
await engine.agentManager.setBridges('agent-abc123', bridgeConfig);
The embedded Fastify server runs locally and the Electron main process communicates via stdio bridge.
// WebSocket — real-time chat stream
const ws = new WebSocket('ws://localhost:PORT/ws/agent-abc123');
ws.send(JSON.stringify({
type: 'chat',
content: 'Summarize my project folder'
}));
ws.onmessage = (event) => {
const msg = JSON.parse(event.data);
// msg.type: 'chunk' | 'tool_call' | 'tool_result' | 'done'
console.log(msg);
};
// HTTP — one-shot task
const res = await fetch('http://localhost:PORT/api/agent/agent-abc123/run', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ task: 'List all .md files on my desk' })
});
const result = await res.json();
# Run all tests
npm test
# Run a specific test file
npx vitest run tests/memory.test.js
# Watch mode
npx vitest
// tests/memory.test.js example pattern
import { describe, it, expect, beforeEach } from 'vitest';
import { MemoryManager } from '../lib/memory/index.js';
describe('MemoryManager', () => {
let memory;
beforeEach(async () => {
memory = new MemoryManager({ agentId: 'test-agent', inMemory: true });
await memory.init();
});
it('stores and retrieves a memory', async () => {
await memory.store({ type: 'fact', content: 'User likes dark mode', importance: 0.9 });
const results = await memory.query({ query: 'dark mode', limit: 5 });
expect(results[0].content).toContain('dark mode');
});
});
# Remove quarantine attribute if right-click → Open doesn't work
xattr -dr com.apple.quarantine /Applications/OpenHanako.app
Cmd+Option+I / Ctrl+Shift+I) → Console for errors// Force a manual compile
await engine.agentManager.getAgent('agent-abc123').memory.compile({ force: true });
// Temporarily disable safety review for trusted local skills only
await skillManager.installLocal({
path: './my-skill',
agentId: 'agent-abc123',
safetyReview: false // ⚠️ only for local dev, never for untrusted sources
});
.exe