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openhanako-personal-ai-agentopenhanako 个人 AIAgent

Agent Skill

openhanako-personal-ai-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

22,239

周安装

936

GitHub Stars

39

下载量

7,788
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openhanako-personal-ai-agent(openhanako 个人 AIAgent)
来源仓库:https://github.com/aradotso/trending-skills
仓库路径:skills/openhanako-personal-ai-agent
安装命令:
npx skills add https://github.com/aradotso/trending-skills --skill openhanako-personal-ai-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/aradotso/trending-skills --skill openhanako-personal-ai-agent

简介

openhanako-personal-ai-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词或任务场景快速定位候选结果时使用。

  • 适用于研究检索类任务,可结合来源仓库和原始 README 核验具体用法。
  • 通过 npx skills add 命令从 GitHub 安装,需确认权限范围和维护状态。
  • 使用前建议检查是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

OpenHanako Personal AI Agent

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.


Installation

Download & Run

# 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"

Build from Source

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

First-Run Onboarding

On first launch, the wizard asks for:

  1. Language — UI language preference
  2. Your name — used by agents when addressing you
  3. Model provider — any OpenAI-compatible endpoint
  4. Three models:

- 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)

Provider Configuration Examples

// 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"
}

Project Architecture

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

Key Managers (via unified engine facade)

ManagerResponsibility
AgentManagerCreate, load, delete agents
SessionManagerConversation sessions per agent
ModelManagerRoute requests to configured providers
PreferencesManagerUser/global settings
SkillManagerInstall, enable, disable, sandbox skills

Agent Configuration

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

Personality Template Example

# 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 System

Skills extend agent capabilities. They live in skills2set/ (built-in) or are installed per-agent.

Install a Skill from GitHub

// 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
});

Skill Definition Format (SKILL.md → skills2set)

---
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

Writing a Custom Skill (JavaScript)

// 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
        };
      }
    }
  ]
};

Memory System

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();

Memory Tiers

TierStorageDecay
Working memoryworking.db (SQLite)Fast — recent N turns
Compiled memorycompiled.mdSlow — summarized by utility-large model
Desk notes (Jian)Files on deskManual / no decay

Built-in Tools

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' } }

Sandbox Access Tiers (PathGuard)

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.


Multi-Agent Setup

// 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
});

Scheduled Tasks (Cron & Heartbeat)

// 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();

Multi-Platform Bridge

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);

Server API (Fastify + WebSocket)

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();

Testing

# 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');
  });
});

Troubleshooting

App won't open on macOS

# Remove quarantine attribute if right-click → Open doesn't work
xattr -dr com.apple.quarantine /Applications/OpenHanako.app

Agent not responding

  • Check that the API key env var is set and the base URL is reachable
  • Open DevTools (Cmd+Option+I / Ctrl+Shift+I) → Console for errors
  • Verify the model name matches exactly what your provider supports

Memory compilation not triggering

// Force a manual compile
await engine.agentManager.getAgent('agent-abc123').memory.compile({ force: true });

Skill installation blocked by safety review

// 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
});

Sandbox permission denied

  • Check the PathGuard tier for the path being accessed
  • Use the desktop UI: Agent Settings → Sandbox → Grant Path Access
  • Or programmatically request elevation to Tier 3 (prompts user confirmation)

Windows Defender false positive on built .exe

  • The installer is unsigned; click More info → Run anyway in SmartScreen
  • Add an exclusion in Windows Security if needed during development

Key Links

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.63%
按下载量换算2,853

Claude

28.85%
按下载量换算2,247

Cursor

21.99%
按下载量换算1,713

Gemini CLI

10.32%
按下载量换算804

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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