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Agent Skill · 研究检索

workflow-test-fix-cycle(工作流程测试修复周期)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

workflow-test-fix-cycle 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,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 39,878。

总安装 1,354周安装 57GitHub Stars 1,935下载 474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:workflow-test-fix-cycle(工作流程测试修复周期)
来源仓库:https://github.com/catlog22/claude-code-workflow
仓库路径:skills/workflow-test-fix-cycle
安装命令:
npx skills add https://github.com/catlog22/claude-code-workflow --skill workflow-test-fix-cycle
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/catlog22/claude-code-workflow --skill workflow-test-fix-cycle

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。

用于辅助测试设计、自动化测试、用例整理和回归验证,帮助编写或修复测试代码。可生成单元测试、端到端测试或根据失败日志定位问题,但需避免为通过测试而破坏逻辑。使用前需确认项目测试框架、运行命令和夹具数据,区分本地模拟与生产环境。涉及浏览器或外部服务时,应明确使用测试环境与模拟方式,防止误操作。

workflow-test-fix-cycle 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/workflow-test-fix-cycle

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/catlog22/claude-code-workflow --skill workflow…;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

    它需要需要联网,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

workflow-test-fix-cycle 怎么安装?

在终端执行 npx skills add https://github.com/catlog22/claude-code-workflow --skill workflow-test-fix-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

workflow-test-fix-cycle 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。

workflow-test-fix-cycle 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

workflow-test-fix-cycle 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。

workflow-test-fix-cycle 用的人多吗?

公开数据是累计安装 1,354 次,近一周安装 57 次,下载 474 次,GitHub 1,935 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。

workflow-test-fix-cycle 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 1,935 星,维护活跃度相对可查。

先想清楚的地方

  • 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

  • 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
workflow-test-fix-cycle

工作流程测试修复周期 · 本页

1,3541,935需要联网未明确通过

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

Workflow Test-Fix Cycle

End-to-end test-fix workflow pipeline: generate test sessions with progressive layers (L0-L3), AI code validation, and task generation (Phase 1), then execute iterative fix cycles with adaptive strategy engine until pass rate >= 95% (Phase 2).

Architecture Overview

┌────────────────────────────────────────────────────────────────────────────┐
│  Workflow Test-Fix Cycle Orchestrator (SKILL.md)                            │
│  → Full pipeline: Test generation + Iterative execution                     │
│  → Phase dispatch: Read phase docs, execute, pass context                   │
└───────────────┬────────────────────────────────────────────────────────────┘
                │
   ┌────────────┴────────────────────────┐
   ↓                                     ↓
┌─────────────────────────┐   ┌─────────────────────────────┐
│ Phase 1: Test-Fix Gen   │   │ Phase 2: Test-Cycle Execute  │
│ phases/01-test-fix-gen  │   │ phases/02-test-cycle-execute │
│ 5 sub-phases:           │   │ 3 stages:                    │
│ ① Create Session        │   │ ① Discovery                  │
│ ② Gather Context        │   │ ② Main Loop (iterate)        │
│ ③ Test Analysis (Gemini)│   │ ③ Completion                 │
│ ④ Generate Tasks        │   │                              │
│ ⑤ Summary               │   │ Agents (via spawn_agent):    │
│                         │   │ @cli-planning-agent           │
│ Agents (via spawn_agent)│   │ @test-fix-agent               │
│ @test-context-search    │   │                              │
│ @context-search         │   │ Strategy: conservative →      │
│ @cli-execution          │   │ aggressive → surgical          │
│ @action-planning        │   │                              │
└────────┬────────────────┘   └────────────┬──────────────────┘
         ↓                                 ↓
   IMPL-001..002.json              Pass Rate >= 95%
   TEST_ANALYSIS_RESULTS.md        Auto-complete session

Task Pipeline:
┌──────────────┐    ┌─────────────────┐    ┌─────────────────┐    ┌──────────────┐
│  IMPL-001    │───→│  IMPL-001.3     │───→│  IMPL-001.5     │───→│  IMPL-002    │
│  Test Gen    │    │  Code Validate  │    │  Quality Gate   │    │  Test & Fix  │
│  L1-L3       │    │  L0 + AI Issues │    │  Coverage 80%+  │    │  Max 10 iter │
│@code-developer│   │ @test-fix-agent │    │ @test-fix-agent │    │@test-fix-agent│
└──────────────┘    └─────────────────┘    └─────────────────┘    └──────────────┘
                                                                        │
                                                              Fix Loop: │
                                                    ┌──────────────────┘
                                                    ↓
                                              ┌──────────┐
                                              │ @cli-plan│───→ IMPL-fix-N.json
                                              │  agent   │
                                              ├──────────┤
                                              │@test-fix │───→ Apply & re-test
                                              │  agent   │
                                              └──────────┘

Key Design Principles

  1. Two-Phase Pipeline: Generation (Phase 1) creates session + tasks, Execution (Phase 2) runs iterative fix cycles
  2. Pure Orchestrator: Dispatch to phase docs, parse outputs, pass context between phases
  3. Phase 1 Auto-Continue: Sub-phases within Phase 1 run autonomously
  4. Subagent Lifecycle: Explicit lifecycle management with spawn_agent → wait_agent → close_agent
  5. Progressive Test Layers: L0 (Static) → L1 (Unit) → L2 (Integration) → L3 (E2E)
  6. AI Code Issue Detection: Validates against common AI-generated code problems
  7. Intelligent Strategy Engine: conservative → aggressive → surgical based on iteration context
  8. CLI Fallback Chain: Gemini → Qwen → Codex for analysis resilience
  9. Progressive Testing: Affected tests during iterations, full suite for final validation
  10. Role Path Loading: Subagent roles loaded via path reference in MANDATORY FIRST STEPS

Auto Mode

Phase 1 generates test session and tasks. Phase 2 executes iterative fix cycles until pass rate >= 95% or max iterations reached. Between Phase 1 and Phase 2, you MUST stop and wait for user confirmation before proceeding to execution. Phase 2 runs autonomously once approved.

Subagent API Reference

spawn_agent

Create a new subagent with task assignment.

const agentId = spawn_agent({
  agent_type: "{agent_type}",
  message: `
## TASK ASSIGNMENT

### MANDATORY FIRST STEPS (Agent Execute)
1. Run: `ccw spec load --category "planning execution"`

## TASK CONTEXT
${taskContext}

## DELIVERABLES
${deliverables}
`
})

wait_agent

Get results from subagent (only way to retrieve results).

const result = wait_agent({
  timeout_ms: 1800000  // 30 minutes
})

if (result.timed_out) {
  followup_task({ target: agentId, message: "STATUS_CHECK: Report current progress, findings so far, and estimated remaining work." })
  const status = wait_agent({ timeout_ms: 180000 })  // 3 min
  if (status.timed_out) {
    followup_task({ target: agentId, message: "FINALIZE: Output all current findings immediately. Time limit reached.", interrupt: true })
    const forced = wait_agent({ timeout_ms: 180000 })  // 3 min
    if (forced.timed_out) {
      close_agent({ target: agentId })
    }
  }
}

followup_task

Assign new work to active subagent (for clarification or follow-up).

followup_task({
  target: agentId,
  message: `
## CLARIFICATION ANSWERS
${answers}

## NEXT STEP
Continue with plan generation.
`
})

close_agent

Clean up subagent resources (irreversible).

close_agent({ target: agentId })

Usage

workflow-test-fix-cycle <input> [options]

# Input (Phase 1 - Test Generation)
source-session-id    WFS-* session ID (Session Mode - test validation for completed implementation)
feature description  Text description of what to test (Prompt Mode)
/path/to/file.md     Path to requirements file (Prompt Mode)

# Options (Phase 2 - Cycle Execution)
--max-iterations=N   Custom iteration limit (default: 10)

# Examples
workflow-test-fix-cycle WFS-user-auth-v2                                              # Session Mode
workflow-test-fix-cycle "Test the user authentication API endpoints in src/auth/api.ts" # Prompt Mode - text
workflow-test-fix-cycle ./docs/api-requirements.md                                     # Prompt Mode - file
workflow-test-fix-cycle "Test user registration" --max-iterations=15                    # With custom iterations

# Resume (Phase 2 only - session already created)
workflow-test-fix-cycle --resume-session="WFS-test-user-auth"                          # Resume interrupted session

Quality Gate: Test pass rate >= 95% (criticality-aware) or 100% Max Iterations: 10 (default, adjustable) CLI Tools: Gemini → Qwen → Codex (fallback chain)

Test Strategy Overview

Progressive Test Layers (L0-L3):

LayerNameFocus
L0Static AnalysisCompilation, imports, types, AI code issues
L1Unit TestsFunction/class behavior (happy/negative/edge cases)
L2Integration TestsComponent interactions, API contracts, failure modes
L3E2E TestsUser journeys, critical paths (optional)

Key Features:

  • AI Code Issue Detection - Validates against common AI-generated code problems (hallucinated imports, placeholder code, mock leakage, etc.)
  • Project Type Detection - Applies appropriate test templates (React, Node API, CLI, Library, etc.)
  • Quality Gates - IMPL-001.3 (code validation) and IMPL-001.5 (test quality) ensure high standards

Detailed specifications: See the test-task-generate workflow tool for complete L0-L3 requirements and quality thresholds.

Execution Flow

Input → Detect Mode (session | prompt | resume)
  │
  ├─ resume mode → Skip to Phase 2
  │
  └─ session/prompt mode → Phase 1
       │
Phase 1: Test-Fix Generation (phases/01-test-fix-gen.md)
  ├─ Sub-phase 1.1: Create Test Session → testSessionId
  ├─ Sub-phase 1.2: Gather Test Context (spawn_agent) → contextPath
  ├─ Sub-phase 1.3: Test Generation Analysis (spawn_agent → Gemini) → TEST_ANALYSIS_RESULTS.md
  ├─ Sub-phase 1.4: Generate Test Tasks (spawn_agent) → IMPL-*.json, IMPL_PLAN.md, TODO_LIST.md
  └─ Sub-phase 1.5: Phase 1 Summary
       │
  ⛔ MANDATORY CONFIRMATION GATE
  │   Present plan summary → request_user_input → User approves/cancels
  │   NEVER auto-proceed to Phase 2
       │
Phase 2: Test-Cycle Execution (phases/02-test-cycle-execute.md)
  ├─ Discovery: Load session, tasks, iteration state
  ├─ Main Loop (for each task):
  │   ├─ Execute → Test → Calculate pass_rate
  │   ├─ 100% → SUCCESS: Next task
  │   ├─ 95-99% + low criticality → PARTIAL SUCCESS: Approve
  │   └─ <95% → Fix Loop:
  │       ├─ Select strategy: conservative/aggressive/surgical
  │       ├─ spawn_agent(@cli-planning-agent) → IMPL-fix-N.json
  │       ├─ spawn_agent(@test-fix-agent) → Apply fix & re-test
  │       └─ Re-test → Back to decision
  └─ Completion: Final validation → Summary → Sync session state → Auto-complete session

Core Rules

  1. Start Immediately: First action is functions.update_plan initialization
  2. No Preliminary Analysis: Do not read files before Phase 1
  3. Parse Every Output: Extract data from each phase/sub-phase for the next
  4. Within-Phase Auto-Continue: Sub-phases within a phase run automatically; Phase 2 iterations run automatically once started
  5. Phase Loading: Read phase doc on-demand (phases/01-*.md, phases/02-*.md)
  6. Task Attachment Model: Sub-tasks ATTACH → execute → COLLAPSE
  7. MANDATORY CONFIRMATION GATE: After Phase 1 completes, you MUST stop and present the generated plan to the user. Wait for explicit user approval via request_user_input before starting Phase 2. NEVER auto-proceed from Phase 1 to Phase 2
  8. Phase 2 Continuous: Once user approves, Phase 2 runs continuously until pass rate >= 95% or max iterations reached
  9. Explicit Lifecycle: Always close_agent after wait_agent completes to free resources

Phase Execution

Phase 1: Test-Fix Generation

Read: phases/01-test-fix-gen.md

5 sub-phases that create a test session and generate task JSONs:

  1. Create Test Session → testSessionId
  2. Gather Test Context (spawn_agent → wait_agent → close_agent) → contextPath
  3. Test Generation Analysis (spawn_agent → wait_agent → close_agent) → TEST_ANALYSIS_RESULTS.md
  4. Generate Test Tasks (spawn_agent → wait_agent → close_agent) → IMPL-001.json, IMPL-001.3.json, IMPL-001.5.json, IMPL-002.json, IMPL_PLAN.md, TODO_LIST.md
  5. Phase 1 Summary → ⛔ MANDATORY: Present plan and wait for user confirmation before Phase 2

Agents Used (via spawn_agent):

  • test_context_search_agent (agent_type: test_context_search_agent) - Context gathering (Session Mode)
  • context_search_agent (agent_type: context_search_agent) - Context gathering (Prompt Mode)
  • cli_execution_agent (agent_type: cli_execution_agent) - Test analysis with Gemini
  • action_planning_agent (agent_type: action_planning_agent) - Task JSON generation

Phase 2: Test-Cycle Execution

Read: phases/02-test-cycle-execute.md

3-stage iterative execution with adaptive strategy:

  1. Discovery - Load session, tasks, iteration state
  2. Main Loop - Execute tasks → Test → Analyze failures → Fix → Re-test
  3. Completion - Final validation → Summary → Auto-complete session

Agents Used (via spawn_agent):

  • cli_planning_agent (agent_type: cli_planning_agent) - Failure analysis, root cause extraction, fix task generation
  • test_fix_agent (agent_type: test_fix_agent) - Test execution, code fixes, criticality assignment

Strategy Engine: conservative (iteration 1-2) → aggressive (pass >80%) → surgical (regression)

Output Artifacts

Directory Structure

{projectRoot}/.workflow/active/WFS-test-[session]/
├── workflow-session.json              # Session metadata
├── IMPL_PLAN.md                       # Test generation and execution strategy
├── TODO_LIST.md                       # Task checklist
├── .task/
│   ├── IMPL-001.json                  # Test understanding & generation
│   ├── IMPL-001.3-validation.json     # Code validation gate
│   ├── IMPL-001.5-review.json         # Test quality gate
│   ├── IMPL-002.json                  # Test execution & fix cycle
│   └── IMPL-fix-{N}.json             # Generated fix tasks (Phase 2)
├── .process/
│   ├── [test-]context-package.json    # Context and coverage analysis
│   ├── TEST_ANALYSIS_RESULTS.md       # Test requirements and strategy (L0-L3)
│   ├── iteration-state.json           # Current iteration + strategy + stuck tests
│   ├── test-results.json              # Latest results (pass_rate, criticality)
│   ├── test-output.log                # Full test output
│   ├── fix-history.json               # All fix attempts
│   ├── iteration-{N}-analysis.md      # CLI analysis report
│   └── iteration-{N}-cli-output.txt
└── .summaries/iteration-summaries/

Progress Tracking

Initialization (MANDATORY)

// Initialize progress tracking after input parsing
functions.update_plan([
  { id: "phase-1", title: "Phase 1: Test-Fix Generation", status: "in_progress" },
  { id: "phase-2", title: "Phase 2: Test-Cycle Execution", status: "pending" }
])

Phase Transitions

// After Phase 1 completes (before mandatory confirmation gate)
functions.update_plan([
  { id: "phase-1", status: "completed" },
  { id: "phase-2", status: "in_progress" }
])

// After Phase 2 completes (pass rate >= 95% or max iterations)
functions.update_plan([{ id: "phase-2", status: "completed" }])

Resume Mode

// When --resume-session skips Phase 1
functions.update_plan([
  { id: "phase-1", title: "Phase 1: Test-Fix Generation", status: "completed" },
  { id: "phase-2", title: "Phase 2: Test-Cycle Execution", status: "in_progress" }
])

Error Handling

PhaseScenarioAction
1.1Source session not found (session mode)Return error with session ID
1.1No completed IMPL tasks (session mode)Return error, source incomplete
1.2Context gathering failedReturn error, check source artifacts
1.2Agent timeoutRetry with extended timeout, close_agent, then return error
1.3Gemini analysis failedReturn error, check context package
1.4Task generation failedRetry once, then return error
2Test execution errorLog, retry with error context
2CLI analysis failureFallback: Gemini → Qwen → Codex → manual
2Agent execution errorSave state, close_agent, retry with simplified context
2Max iterations reachedGenerate failure report, mark blocked
2Regression detectedRollback last fix, switch to surgical strategy
2Stuck tests detectedContinue with alternative strategy, document in failure report

Lifecycle Error Handling:

try {
  const agentId = spawn_agent({ message: "..." });
  const result = wait_agent({ timeout_ms: 1800000 });  // 30 minutes
  // ... process result ...
  close_agent({ target: agentId });
} catch (error) {
  if (agentId) close_agent({ target: agentId });
  throw error;
}

Coordinator Checklist

Phase 1 (Generation):

  • Detect input type (session ID / description / file path / resume)
  • Initialize functions.update_plan with 2 top-level phases
  • Read phases/01-test-fix-gen.md for detailed sub-phase execution
  • Execute 5 sub-phases with spawn_agent → wait_agent → close_agent lifecycle
  • Verify all Phase 1 outputs (4+ task JSONs, IMPL_PLAN.md, TODO_LIST.md)
  • Ensure all agents are closed after each sub-phase completes
  • ⛔ MANDATORY: Present plan summary and request_user_input for confirmation

- Show: session ID, task count, test layers, quality gates - Options: "Proceed to Execution" / "Review Plan" / "Cancel" - If "Cancel" → return, do NOT start Phase 2 - If "Review Plan" → display IMPL_PLAN.md, then return - Only proceed to Phase 2 if user selects "Proceed to Execution"

Phase 2 (Execution):

  • Read phases/02-test-cycle-execute.md for detailed execution logic
  • Load session state and task queue
  • Execute iterative test-fix cycles with spawn_agent → wait_agent → close_agent
  • Track iterations via functions.update_plan
  • Auto-complete session on success (pass rate >= 95%)
  • Ensure all agents are closed after each iteration

Resume Mode:

  • If --resume-session provided, skip Phase 1
  • Load existing session directly into Phase 2

Related Skills

Prerequisite Skills:

  • workflow-plan or workflow-execute - Complete implementation (Session Mode)
  • None for Prompt Mode

Phase 1 Agents (used by phases/01-test-fix-gen.md via spawn_agent):

  • test_context_search_agent (agent_type: test_context_search_agent) - Test coverage analysis (Session Mode)
  • context_search_agent (agent_type: context_search_agent) - Codebase analysis (Prompt Mode)
  • cli_execution_agent (agent_type: cli_execution_agent) - Test requirements with Gemini
  • action_planning_agent (agent_type: action_planning_agent) - Task JSON generation

Phase 2 Agents (used by phases/02-test-cycle-execute.md via spawn_agent):

  • cli_planning_agent (agent_type: cli_planning_agent) - CLI analysis, root cause extraction, task generation
  • test_fix_agent (agent_type: test_fix_agent) - Test execution, code fixes, criticality assignment

Follow-up:

  • Session sync: $session-sync -y "Test-fix cycle complete: {pass_rate}% pass rate"
  • Session auto-complete on success
  • Issue creation for follow-up work (post-completion expansion)

平台分布

Codex

35.42%
按下载量换算168

Claude

32.08%
按下载量换算152

Cursor

21.07%
按下载量换算100

Gemini CLI

9.42%
按下载量换算45

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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