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Ai Autotester
作者
jason513597
· GitHub ↗
· v1.0.0
470
总下载
0
收藏
4
当前安装
1
版本数
在 OpenClaw 中安装
/install ai-autotester
功能描述
Automates code testing by analyzing tasks, planning subtasks, executing tests, validating results, and providing detailed reports and summaries.
使用说明 (SKILL.md)
AI_AutoTester
Purpose
自動化測試程式碼
Primary Agents
Tester
Notes
單獨測試或流程節點
Inputs
- task: 要執行的任務描述
- context: 額外上下文(可選)
- constraints: 限制條件(可選)
Outputs
- plan/result/report(依任務類型)
- logs/summary
Workflow (default)
- Analyze task
- Plan subtasks
- Execute by role
- Validate result
- Return final summary
Safety
- 不執行破壞性操作,除非明確授權
- 外部動作(發送、部署到正式環境)需二次確認
- 記錄關鍵決策與錯誤
安全使用建议
Before installing or running this skill: (1) Be aware that run.py will write files into the target project (tests/test_smoke.py and requirements-test.txt), run pip to install packages (which will reach out to PyPI or other URLs listed in requirements.txt), and execute pytest — so it will execute code from the target repository. (2) The script assumes a hardcoded workspace path (/home/jason/.openclaw/workspace) unless you pass an absolute path; this is undocumented and may not match your environment. (3) Running this against untrusted code can execute arbitrary/malicious code or cause network requests to attacker-controlled locations — run it inside an isolated container, sandbox, or CI runner with network restrictions. (4) The code contains a small bug (uses datetime.UTC which will raise an error) — expect potential runtime failures. Recommended actions: review the target project's requirements.txt for suspicious package sources, run the tester on a copy of the repo in an isolated environment, or request a version of the skill that accepts a configurable workspace path and documents the file-write and install behavior.
功能分析
Type: OpenClaw Skill
Name: ai-autotester
Version: 1.0.0
The AI_AutoTester skill is a functional utility for running automated Python tests. The run.py script sets up a testing environment, installs dependencies via pip, and executes pytest on a target directory. While it contains a hardcoded workspace path (/home/jason/.openclaw/workspace) and executes shell commands via subprocess, these actions are consistent with the stated purpose of a testing tool and show no evidence of malicious intent, data exfiltration, or unauthorized access.
能力评估
Purpose & Capability
The skill name/description (automated testing) aligns with the included run.py which prepares tests and runs pytest. However the code hardcodes a workspace path (/home/jason/.openclaw/workspace) and resolves the target relative to it unless an absolute path is provided. The SKILL.md does not mention this workspace assumption; that hardcoded path is unexpected and may not match the user's environment.
Instruction Scope
SKILL.md describes analyzing, planning, executing, and validating tests but does not disclose that the shipped run.py will: create a tests/ directory and write a test_smoke.py file into the target project, write a requirements-test.txt into the project, invoke pip to install requirements (both the project's requirements.txt and a created requirements-test.txt), and execute pytest. These are side effects (file writes, installs, executing arbitrary project code) that are not documented in SKILL.md.
Install Mechanism
There is no install spec; the skill is instruction-only plus a small Python helper. Nothing is downloaded by the skill manifest itself. The code does call pip at runtime to install packages, but that's runtime behavior rather than an installer provided by the skill bundle.
Credentials
The skill declares no required environment variables or config paths, yet the code implicitly depends on and writes under a hardcoded filesystem location (/home/jason/.openclaw/workspace). It will also run pip to pull packages from PyPI or remote URLs referenced in requirements.txt — granting network access to fetch arbitrary packages. Those capabilities are reasonable for running tests but are not reflected in the metadata or SKILL.md and therefore are disproportionate to the documented requirements.
Persistence & Privilege
always is false and the skill does not request persistent/system-wide privileges. It does modify the target project (creates tests/ and requirements-test.txt) which is expected for a test scaffold but should be considered a write operation to user files.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ai-autotester - 安装完成后,直接呼叫该 Skill 的名称或使用
/ai-autotester触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
AI_AutoTester 1.0.0 初始發佈:
- 提供自動化測試程式碼的功能
- 支援單獨測試與流程節點
- 接收任務描述、上下文與限制條件輸入
- 產出計畫、結果、報告及測試日誌摘要
- 標準工作流程:分析任務、規劃子任務、角色執行、驗證結果、彙整回報
- 內建安全機制:避免未授權破壞性操作、重要外部動作需二次確認、決策與錯誤皆有記錄
元数据
常见问题
Ai Autotester 是什么?
Automates code testing by analyzing tasks, planning subtasks, executing tests, validating results, and providing detailed reports and summaries. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 470 次。
如何安装 Ai Autotester?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-autotester」即可一键安装,无需额外配置。
Ai Autotester 是免费的吗?
是的,Ai Autotester 完全免费(开源免费),可自由下载、安装和使用。
Ai Autotester 支持哪些平台?
Ai Autotester 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Ai Autotester?
由 jason513597(@jason513597)开发并维护,当前版本 v1.0.0。
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