ai-assist-test-audit

审查 · 58
已收录

16-dimension test suite audit with depth control (quick/standard/deep), gap matrix, and health scoring. Covers coverage, quality, mocking, data management, CI/CD, performance, mutation testing, and modern patterns. Use when evaluating test suite quality, identifying testing gaps,

Verified installs0
Stars88
版本1.0.0
质量61/100 · 有潜力
信任58/100 · Do not auto-install
审计73/100 · 需审查

供给资产档案

研究与知识工作

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

浏览赛道

场景

研究 Agent

I need my agent to research a topic, compare sources, and produce a concise report.

适配 Agent

Claude Code + CLI + Codex

适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。

安装

就绪

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit

维护状态

新鲜

距上次推送 2 天

风险

需审查

许可证不清晰

GitHub 质量

88

61/100 质量 · 66/100 信任

覆盖标签

研究研究 Agent安全agent-skill

审查说明

许可证不清晰 · Financial research output is not financial advice; require human review before any live investment decision

Agent 采用评分卡

一眼查看信任、审计与安装准备度

这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。

质量

有潜力
61

有用的候选项,但采用前应与替代方案比较。

信任

Do not auto-install
58

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

审计

需审查
73

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

OpenAgentSkill 信任评分 v5

安装前需人工审查

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

88 个 GitHub Stars

仓库活跃度

88 个 Star,12 个 Fork

维护状态

距上次推送 2 天

许可证

未知

安装

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit

安装安全性

标准软件包或运行时安装路径

权限范围

filesystem or document access, network or browser access

Agent 结果

暂未有 Agent 结果数据

文档

Usable metadata, review docs

风险摘要

生产前审查

  • Repository license is unknown; consider adding a license file for clarity.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • 许可证不清晰
  • Quality score needs review

安装准备度

安装路径可用

  • 安装路径可用
  • 仓库证据可用
  • 许可证不清晰
  • 暂无 Agent 验证结果证据

Agent 可读元数据

这个 Skill 的机器可读决策数据。

使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。

打开 JSON

适用任务

  • 研究 Agent 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects
  • 检索来源

适用 Agent

CodexClaude CodeCursorOpenAgentSkill CLICLI

安装决策

命令
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit
策略
审查
人工审查

信任与风险

信任
58/100
审计
73/100
风险级别
需审查

结果闭环

端点
/api/agent/outcome
事件 ID
resolve
结果
5

安装命令

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit

不适用场景

  • 需要厂商支持 SLA 的团队
  • production agents without a repository review
  • Repository license is unknown; consider adding a license file for clarity.
  • 许可证不清晰
  • Financial research output is not financial advice; require human review before any live investment decision

Agent 安全 v2

57/100 · 安装前审查

实验性审查

Sparse or mixed signals. Useful for discovery, but not for autonomous installation.

Test manually in an isolated workspace and compare against safer alternatives.

通过 API 解析

网络访问

Skill 可能访问远程页面、API、仓库或外部服务。

文件系统访问

Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。

  • 许可证不清晰

安装目标

在你的 Agent 工作流中安装此 Skill

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-test-audit

Agent 解析计划

让 Agent 在安装前验证匹配度。

Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。

打开文本计划

Agent 应检查

  • 从 Resolve API 检查任务匹配与替代方案。
  • 检查审计评分、信任评分和安全策略警告。
  • 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。

复制提示词

Task: Use ai-assist-test-audit in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-test-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-test-audit/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent 交接

把安装路径交给 Agent,而不是再给一个目录页。

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

打开安装 API

Agent 提示词

Use ai-assist-test-audit for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-test-audit/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit

Registry 元数据

用于自动选择 Skill 的 Agent 可读档案。

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。

打开 Manifest

适配 Agent

61/100

研究 Agent

平台

Claude Code

审计报告

需审查 · 73/100

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

查看审计报告查看评估报告

Agent 决策面板

Fallback candidate for Research agents

先用此 Skill 做原型验证,并保留备选方案。

61
就绪度
原型验证
阶段

栈中角色

备选候选

主要匹配

研究 Agent

信任标签

先做原型验证

安装路径

命令已就绪

适用场景

  • 研究 Agent 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects

证据

  • 仓库近期活跃
  • 已提供安装命令或 GitHub 仓库
  • 61/100 质量档案
  • 3 个 OpenAgentSkill 交互事件

先审查

  • Repository license is unknown; consider adding a license file for clarity.

实施路径

  1. 1在沙盒 Agent 中安装它,并端到端完成一次研究 Agent任务。
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

信任档案

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

58
OpenAgentSkill 信任评分

GitHub 采用度

检查

88 个 GitHub Stars

Star/Fork 活跃度

检查

88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息

近期维护

通过

距上次推送 2 天

许可证清晰度

检查

未知

积极信号

  • AI 审查已通过
  • 安装路径可用
  • 仓库证据可用
  • 近期维护的仓库
  • 安装命令未发现明显高风险模式
  • 结果闭环已就绪,但需要首次真实 Agent 运行

安装前审查

  • Repository license is unknown; consider adding a license file for clarity.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • 许可证不清晰
  • Quality score needs review
  • GitHub adoption: 88 GitHub stars
  • Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • 暂未有真实 Agent 结果报告
  • 无人值守安装前需要人工审查

建议操作

Choose a stronger alternative or inspect the source manually before any install attempt.

质量档案

有潜力 适用于 Agent 工作流的候选

有用的候选项,但采用前应与替代方案比较。

61
GitHub Stars
88
新鲜度
2 天前
安装就绪
许可证
未知
安装前审查: Repository license is unknown; consider adding a license file for clarity.

工作流匹配

在这些场景使用此 Skill

工作流匹配

加入完整工作流

替代方案短名单

安装前对比

可能适合该任务的相近 Skill。

对比全部

概览

--- name: ai-assist-test-audit description: "16-dimension test suite audit with depth control (quick/standard/deep), gap matrix, and health scoring. Covers coverage, quality, mocking, data management, CI/CD, performance, mutation testing, and modern patterns. Use when evaluating test suite quality, identifying testing gaps, or assessing test infrastructure health." argument-hint: "[quick|standard|deep] [scope]" ---

# TEST AUDIT

**Objective:** Produce a severity-ranked test suite assessment with deterministic metrics, gap matrix, health score, and remediation plan across 16 dimensions. **When to use:** Evaluating test suite quality, identifying testing gaps, assessing test infrastructure health.

> This skill audits existing tests. To write new tests, ask your AI agent directly.

Start all responses with '🩺 [Test Audit Step X: Name]'

## Role

Test quality specialist evaluating test suites for effectiveness, completeness, and adherence to enterprise-grade standards across 16 dimensions.

## Context

**AGENTS.md check:** If `./AGENTS.md` exists, read it — follow test conventions, patterns, and architecture. Overrides defaults. If missing, warn and proceed.

**Spec awareness:** If `specs/` has active work, verify test changes don't conflict.

**Stack detection:** Detect framework, runner, coverage tool, file patterns, config. Research current best practices for detected stack version.

**Input:** `$ARGUMENTS` — optional depth (quick/standard/deep), focus areas, scope (directory/pattern/all). Default: standard, all applicable dims, entire suite. No test files: "No test suite found. Would you like me to help create tests?"

**Project type:** WEB / API / DIST / PERF / ALL (default). Determines dimension applicability.

## Rules

1. **Run tests before reviewing.** Execute suite for pass/fail, duration, coverage. Incomplete without deterministic metrics. 2. **Test behavior, not implementation.** Flag tests asserting on internal state. 3. **Flakiness is Critical severity.** Any non-deterministic test is worse than no test. 4. **Over-mocking is a code smell.** >50% mock setup lines = testing mocks not code. 5. **Coverage without assertions is theater.** Flag high-coverage with weak assertions. 6. **Adapt to depth.** Quick=3 dims (1,3,14), Standard=12-14 dims, Deep=all 16. 7. **Dimension applicability.** 14 ALL, Contract=API/DIST, Accessibility=WEB. N/A redistributes weight. 8. **Current-year standards.** Research specific framework version docs. 9. **Respect conventions.** AGENTS.md/config choices are not findings. 10. **Evidence required.** File:line, metric output, or code sample for every finding. 11. **Chat-only output.** Present ALL findings, tables, and scores in chat. Never create files without explicit user permission.

## Process

### Step 1: Context & Infrastructure

1. Read AGENTS.md, run `git status`, detect stack (framework, runner, coverage tool) 2. Parse arguments for depth, focus, scope; count test files 3. Determine project type (WEB/API/DIST/PERF/ALL) and active dimensions

> 🩺 [Test Audit Step 1] Suite: [framework] with [tool]. [X] files. Depth: [depth]. Active: [N]/16.

### Step 2: Test Execution

1. Run suite with coverage (confirm with user if side effects uncertain) 2. Record: total, passing, failing, skipped, duration, line/branch/function % 3. If tests fail: note failures, continue audit

> 🩺 [Test Audit Step 2] [X] pass, [Y] fail, [Z] skip. Coverage: [X]% lines, [Y]% branches. [X]s.

### Step 3: Dimension Audit

Read `references/dimensions.md` for the depth mapping table, dimension activation rules, and per-dimension check definitions.

1. Activate dimensions per depth: Quick (1,3,14), Standard (1-8, 11 if API/DIST, 12 if WEB, 13-16), Deep (all 16) 2. Skip N/A dimensions, redistribute weight proportionally 3. Audit each activated dimension using the check definitions 4. Score each dimension

> 🩺 [Test Audit Step 3] Auditing dimension [X/Y]: [Name]...

### Step 4: Gap Matrix

Build module-by-dimension grid showing coverage across the codebase. Columns adapt to depth level: Quick shows Cov/Qual/Edge only, Standard shows all active, Deep shows all 16.

> 🩺 [Test Audit Step 4] Gap matrix: [X] modules, [Y] gaps identified.

### Step 5: Findings & Score

Read `references/scoring.md` for health score calculation, severity definitions, and deterministic metrics thresholds.

Read `references/output-template.md` for finding format, summary table, gap matrix format, positive observations, improvement plan, and fix options.

1. Calculate health score using dimension weights and N/A redistribution 2. Populate deterministic metrics table from actual execution (Step 2) 3. Rank findings by severity (Critical > Warning > Suggestion) 4. Present: finding details, summary table, gap matrix, metrics, positive observations, health score, improvement plan, fix options

### Self-Verification

> Canonical version in `references/output-template.md`. Brief version here for quick reference.

- [ ] Tests executed (or documented why not) - [ ] Metrics from actual output, not estimates - [ ] Every finding has file:line - [ ] Over-mocking verified by reading mock setup - [ ] Gap matrix reflects actual modules - [ ] AGENTS.md conventions respected - [ ] All active dimensions audited - [ ] Weights consistent with depth/N/A redistribution - [ ] Depth mapping correct (Q=3, S=12-14, D=16)

### Session End

> 🩺 [Test Audit Complete] > > **Score:** [XX]/100. Depth: [depth]. Dimensions: [N]/16. > **Findings:** [X] critical, [Y] warnings, [Z] suggestions. > **Metrics:** [X]/[Y] passing, [Z]% coverage, [W]s duration.

**Next steps (ask user — do not auto-execute):** - Save report to `specs/audit-reports/test-audit-<date>.md`? - Implement fixes? (offer fix options by priority) - Create remediation plan? → `/1-plan` with findings as input - Deeper analysis? → `/ai-assist-security-audit`, `/ai-assist-tech-debt`

## Recovery

| Issue | Solution | |-------|----------| | Suite won't run | Audit code quality without execution; note in report | | No coverage tool | Recommend one; audit without coverage metrics | | Tests >5 minutes | --bail or scope to directory; note in report | | No test files | Critical finding; offer to help create tests | | Mutation too slow | Scope to critical modules or skip | | N/A ambiguous | Default ALL; skip Contract/Accessibility only with evidence |

## Important Reminders

**Response format:** Every response starts with `🩺 [Test Audit Step X: Name]`

**Hard rules:** Run tests first (rule 1). Flakiness is Critical (rule 3). Evidence for every finding (rule 10). Metrics from execution, not estimation.

**Process rules:** Adapt to depth (rule 6). Applicability controls activation (rule 7). Gap matrix for all depths. Summary table mandatory. Weights sum to 100 with N/A redistribution.

**Related:** `/ai-assist-security-audit` for security posture, `/ai-assist-observability-audit` for telemetry, `/ai-assist-tech-debt` for codebase health.

技术详情

版本
1.0.0
许可证
Unknown
最近更新
2026年8月21日
发布时间
2026年8月21日

决策摘要

备选候选

61
就绪
原型验证
阶段

仓库近期活跃

审计

安装审查

安装与采用审查

73
需审查
安全性
73/100
维护状态
100/100
安装
92/100
打开完整审计查看评估报告

Agent 验证证据

Agent 验证证据

来自解析、审查、安装和一次小范围运行后的结果报告。

0
已验证
Needs first agent run自动安装: 先审查最近: 未知
成功率
近期失败
结果
0
输出质量
失败
0
不相关
0
安装次数
0
风险拦截
0
需要配置
0
生产环境
0

暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。

安装

加入 Agent 工作流

免费且开源. 在生产 Agent 中安装前请先审查报告。

增长闭环

分享工具包

X

为 ai-assist-test-audit 准备的场景化草稿,可手动发布到 X。

策展说明
ai-assist-test-audit: 16-dimension test suite audit with depth control (quick/standard/deep), gap matrix, and healt...

88 stars

https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit?ref=x
打开 X 草稿
可选:带安装命令的回复
Listing + install path for ai-assist-test-audit:
https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit?ref=x

Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-test-audit
打开回复草稿

收录来源

Registry 收录

可认领

此列表来自公开来源,维护者认领获批前不会标记为官方。

创作者
jparkerweb
收录方
OpenAgentSkill 社区索引

归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。

认领此 Skill

所有者认领

认领此 Skill 页面

这条 Registry 收录 列表归属于 jparkerweb,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。

创作者外链工具包

将证据徽章加入你的 README

在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-test-audit?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-test-audit?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-test-audit?metric=audit&label=Audit)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-test-audit?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-test-audit)

作者

J

jparkerweb

@jparkerweb

平台适配

健康信号

GitHub Stars
88
质量评分
37/100
最近 GitHub 推送
2026年8月20日
框架提示
未知
OpenAgentSkill 浏览量
3
复制安装命令
0
跳转点击
0

社区信号

告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。

信任与安全

Do not auto-install

58
  • GitHub 采用度88 个 GitHub Stars检查
  • Star/Fork 活跃度88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息检查
  • 近期维护距上次推送 2 天通过
  • 许可证清晰度未知检查
  • README/SKILL.md 完整度公开元数据需要更完整的 README/SKILL.md 上下文信息
  • 依赖与运行时风险network or browser surface通过