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Agent Skill · 研究检索

openhanako-personal-ai-agent(openhanako 个人 AIAgent)

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。

openhanako-personal-ai-agent 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 6,419。

总安装 22,239周安装 936GitHub Stars 39下载 7,788核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/openhanako-personal-ai-agent

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/aradotso/trending-skills --skill openhanako-pe…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openhanako-personal-ai-agent 怎么安装?

在终端执行 npx skills add https://github.com/aradotso/trending-skills --skill openhanako-personal-ai-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openhanako-personal-ai-agent 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openhanako-personal-ai-agent 需要什么权限?

权限级别是接触敏感数据。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。

openhanako-personal-ai-agent 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

openhanako-personal-ai-agent 用的人多吗?

公开数据是累计安装 22,239 次,近一周安装 936 次,下载 7,788 次,GitHub 39 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openhanako-personal-ai-agent 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openhanako-personal-ai-agent

openhanako 个人 AIAgent · 本页

22,23939接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

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

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills