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alibabacloud-agentbay-aio-skills阿里云 agentbay aio 技能

Agent Skill

alibabacloud-agentbay-aio-skills 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

261

周安装

11

GitHub Stars

79

下载量

92
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:alibabacloud-agentbay-aio-skills(阿里云 agentbay aio 技能)
来源仓库:https://github.com/aliyun/alibabacloud-aiops-skills
仓库路径:skills/alibabacloud-agentbay-aio-skills
安装命令:
npx skills add https://github.com/aliyun/alibabacloud-aiops-skills --skill alibabacloud-agentbay-aio-skills
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/aliyun/alibabacloud-aiops-skills --skill alibabacloud-agentbay-aio-skills

简介

用于在远程沙箱中执行用户代码,支持 Python、JavaScript 等多种语言。

  • 通过 AgentBay SDK 自动创建隔离环境,返回结构化执行结果。
  • 适用于函数测试、算法验证等场景,避免本地环境污染。
  • 需确保网络可达 AgentBay 服务,且用户代码不应包含高危系统调用。
  • alibabacloud-agentbay-aio-skills 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

AgentBay AIO Skill

How It Works

This skill runs user code in a remote sandbox (not locally) via AgentBay SDK. The entry script scripts/run_code.py handles sandbox creation, code execution, and result parsing automatically.

# Basic execution
python scripts/run_code.py --code "<user_code>" --language python

# Execute from file
python scripts/run_code.py --code-file /path/to/file.py --language python

# Structured JSON output (use this when writing results to files)
python scripts/run_code.py --code "<user_code>" --language python --json

Supported languages: python, javascript, r, java (case-insensitive). Timeout: 60 seconds max (--timeout-s).

Prerequisites

DependencyVersionPurpose
Python>= 3.8Runtime
wuying-agentbay-sdk>= 1.0.0AgentBay SDK for sandbox code execution

Setup

The script requires wuying-agentbay-sdk installed locally. Install it before first use:

pip install wuying-agentbay-sdk

This is the skill's own required dependency — installing it is not a security concern. If run_code.py fails with ModuleNotFoundError: No module named 'agentbay', install the SDK and retry.

Network domains used: agentbay.aliyuncs.com (API endpoint), agentbay.console.aliyun.com (console), mirrors.aliyun.com (PyPI mirror).

API Key Configuration

Run scripts directly without prompting for API Key configuration. Only guide users when the script explicitly reports "Missing API key":

  1. Apply at AgentBay Console
  2. Save to config file: ~/.config/agentbay/api_key (macOS/Linux) or %USERPROFILE%\.config\agentbay\api_key (Windows)

Execution Rules

CRITICAL: All user code MUST run through scripts/run_code.py — NEVER execute code directly in the local terminal (e.g., python -c, node -e, timeout... python). This applies even if run_code.py fails on the first attempt.

  • If run_code.py fails with a transient error, retry once before reporting failure.
  • If run_code.py fails with "Missing API key" or ModuleNotFoundError, guide the user to fix the issue (see Setup / API Key Configuration) and retry — do NOT fall back to local execution.
  • NEVER run user code locally as a fallback. Report the error instead.

Do not install packages other than wuying-agentbay-sdk, and do not create virtual environments. The sandbox has its own package environment — the Agent should not attempt to modify it from outside.

Output Handling

Standard output: Exit code 0 = success, results in stdout. Non-zero = failure, error in stderr.

Structured output (--json): Returns {success, result, logs: {stdout, stderr}, error_message}.

Writing results to files: Use --json mode and extract only the result field to write to the target file. This ensures SDK metadata (such as session identifiers or internal request IDs) is not accidentally included in output files, because the raw non-JSON output may contain SDK log lines mixed with actual results.

Reporting results: Quote the script's original output directly. Do not infer, abbreviate, or recalculate values — if output is long, clearly indicate omitted portions but keep quoted values verbatim.

File Download Validation

When saving files generated in the sandbox (e.g., chart images) to the local environment:

  1. Use --json mode and extract the base64 content with Python (json module) — do NOT use shell tools (grep/sed/awk) to extract base64 strings, as they truncate long strings.
  2. Decode with: python -c "import base64,json,sys; d=json.load(sys.stdin); open('out.png','wb').write(base64.b64decode(d['result']))" < output.json
  3. Verify the saved file: size > 0 bytes; for images (PNG/JPEG), check magic bytes (89 50 4E 47 / FF D8 FF).
  4. For chart images, file size should be > 5 KB. A file under 5 KB almost certainly indicates truncated data — re-extract and re-decode.

If verification fails, retry the download. Do not report success with a corrupted file.

Chinese/CJK Character Rendering

The script (run_code.py) automatically handles CJK font configuration for matplotlib code — it detects Chinese/Japanese/Korean characters in user code and injects font installation and configuration before execution. No manual font setup is needed.

When the user's code contains Chinese characters AND uses matplotlib/plt, the Agent should proactively prepend the following font installation block in the --code argument on the first execution (not as a retry), because the sandbox may lack CJK fonts and the script's auto-detection provides a safety net but explicit installation is more reliable:

import subprocess
subprocess.run(['apt-get', 'update', '-qq'], capture_output=True)
subprocess.run(['apt-get', 'install', '-y', '-qq', 'fonts-wqy-microhei'], capture_output=True)
import matplotlib
import matplotlib.font_manager as fm
fm.fontManager.addfont('/usr/share/fonts/truetype/wqy/wqy-microhei.ttc')
fm.fontManager = fm.FontManager()
matplotlib.rcParams['font.family'] = 'WenQuanYi Micro Hei'
matplotlib.rcParams['axes.unicode_minus'] = False

This proactive approach avoids the undetectable failure where Chinese characters render as blank boxes (tofu) in the generated image — since tofu appears only visually in the image and produces no text-based warning in stdout, a retry-based approach cannot reliably detect the problem.

Information Security

Do not output internal environment variable names, API Key values, or SDK debug details in conversation replies. When executing scripts, use --json mode and display only the result and error_message fields to users. The raw SDK output may contain internal fields (session identifiers, request IDs, access credentials) that should not be exposed to users or written to output files.

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

35.28%
按下载量换算32

Claude

30.07%
按下载量换算28

Cursor

17.96%
按下载量换算17

Gemini CLI

8.32%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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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