No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by buer2233 · Codex Skill · ★ 152
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-api-test-skill safe to install? View the security audit →
ai-api-test-skill 简体中文 | English 面向 接口自动化项目的 AI Skill：让 Codex / Claude Code 按固定门禁、固定流程、固定 pytest 闭环来新增和维护接口自动化用例，流程图参考：flowchart/flow.md。 它不是一个普通的提示词模板，而是一套可随仓库分发的工程化 Skill：会先校验任务信息，再按“抓包 / 参考用例 / cURL / Java Controller / pytest 报错”选择路径，最后把接口方法、接口用例和测试验证收敛到同一套规范里。 Skill特色 这个Skill更适合没有接口文档、接口文档不规范、接口链路复杂、历史用例多的大型开发项目。在这类项目里，直接 vibe coding 很容易漏上下文、误改文件或重复封装接口； 的做法是把个人和团队日常编写、维护接口自动化用例的流程复刻成一套可执行的 AI 工作流，再用 思路给 AI 加上明确的边界、门禁和反馈回路。 核心特色集中在 5 点： 前置门禁约束修改边界：强制填写接口方法文件、接口方法位置、接口用例文件、接口用例位置和用例名，避免 AI 不知道写在哪里而大范围改动已有文件。 渐进式披露降低上下文噪音：新增、维护、抓包、参考用例、cURL、Controller、pytest 报错驱动等流程拆成子文档，按任务类型只读取必要规范。 真实流量驱动用例生成：内置抓包服务脚本，把 UI 操作产生的真实请求链路转成可分析的接口自动化输入。 SQLite 接口资产索引：首次全量扫描已有接口 URL 与 method，后续增量追加；AI 可通过数据库毫秒级定位接口方法所在文件和行号，减少大量 调用和 token 消耗。 pytest 闭环验证结果：用例编写完成后必须执行目标 pytest，根据真实报错继续修复，直到通过或明确说明环境问题。 当前默认模板输出风格为 ，可通过调整 、任务门禁和用例模板来适配团队自己的接口自动化编码规范，并作为适配 、、 等框架的基础。 实际编写案例记录 通过AI+SKILL编写自动化测试用例记录 通过AI+SKILL维护用例的测试记录 快速开始 详细的使用手册参考：detailedUserManual.md。 准备环境 | Pyth
| Stars | 152 |
| Forks | 18 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 58.6294602812054/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-07 |
| Created | 2026-04-28 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~13k |
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ai-api-test-skill is AI接口自动化测试 Skill：面向 Python + pytest + requests，驱动 Codex / Claude Code 生成、维护和调试接口用例（AI API test automation skill for Python + pytest + requests）. It is categorized as a Codex Skill with 152 GitHub stars.
ai-api-test-skill is primarily written in Python. It covers topics such as ai-api-testing, ai-testing, api-automation.
You can find installation instructions and usage details in the ai-api-test-skill GitHub repository at github.com/buer2233/ai-api-test-skill. The project has 152 stars and 18 forks, indicating an active community.
ai-api-test-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-api-test-skill on Agent Skills Hub include lazy-bird, qaskills, metis. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: