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Agent Skill · 研究检索

iterative-loop(迭代循环)

iterative-loop 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

iterative-loop 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,权限为执行命令;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 66,285。

总安装 267周安装 11GitHub Stars 329下载 87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
MIT

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:iterative-loop(迭代循环)
来源仓库:https://github.com/proffesor-for-testing/agentic-qe
仓库路径:skills/iterative-loop
安装命令:
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill iterative-loop
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill iterative-loop

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。

用于查找、检索和筛选相关信息,快速定位候选结果。适合在关键词、任务场景或来源线索明确时使用。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态,以及是否会触发联网或命令执行。注意检查是否会触发文件读写或高风险操作。

iterative-loop 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/iterative-loop

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/proffesor-for-testing/agentic-qe --skill itera…;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

    它需要执行命令,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

iterative-loop 怎么安装?

在终端执行 npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill iterative-loop。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

iterative-loop 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。

iterative-loop 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill iterative-loop;npx skills add proffesor-for-testing/agentic-qe --skill "iterative-loop" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

iterative-loop 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

iterative-loop 用的人多吗?

公开数据是累计安装 267 次,近一周安装 11 次,下载 87 次,GitHub 329 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。

iterative-loop 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
iterative-loop

迭代循环 · 本页

267329执行命令MIT有提醒

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

Iterative Loop

Overview

The Iterative Loop skill implements continuous AI-driven development loops that persist until completion criteria are met. Inspired by the Ralph Wiggum technique, this approach enables autonomous, self-correcting development cycles where the AI sees its previous work in files and git history, iteratively improving until success.

Core Philosophy

  1. Iteration > Perfection - Don't aim for perfect on first try; let the loop refine the work
  2. Failures Are Data - Each failure provides information to improve the next attempt
  3. Clear Criteria - Success must be objectively measurable (tests, metrics, validations)
  4. Persistence Wins - Keep trying until success; the loop handles retry logic automatically

Prerequisites

  • Claude Code with session management
  • Clear completion criteria (tests, linting, metrics)
  • Version control (git) for tracking iterations

Quick Start

Basic Iterative Development Pattern

# Define task with clear completion criteria
TASK="Implement user authentication with JWT.
Success criteria:
- All unit tests pass
- Integration tests pass
- No TypeScript errors
- Security audit passes
Output <promise>COMPLETE</promise> when all criteria met."

# Execute iterative loop (conceptual)
while ! task_complete; do
  claude_execute "$TASK"
  check_completion_criteria
done

AQE v3 Integration Example

# Using claude-flow hooks for iterative task
npx --no-install ruflo hooks pre-task --description "Implement auth with iteration" --taskId "auth-impl"

# Store iteration state in memory
npx --no-install ruflo memory store \
  --key "iteration-auth" \
  --value '{"iteration": 1, "maxIterations": 20, "criteria": "all tests pass"}' \
  --namespace iterations

Step-by-Step Guide

Step 1: Define Clear Success Criteria

Essential: Every iterative task MUST have objectively measurable completion criteria.

Good Criteria Examples:

✅ All unit tests pass (npm test returns exit code 0)
✅ Coverage > 80% (coverage report shows 80%+)
✅ No TypeScript errors (tsc --noEmit returns 0)
✅ Linting passes (eslint returns 0)
✅ Performance < 100ms (benchmark shows < 100ms)

Bad Criteria Examples:

❌ "Code looks good" (subjective)
❌ "Works properly" (undefined)
❌ "Well-structured" (no measurable check)

Step 2: Structure the Task with Phases

Break complex tasks into incremental phases:

## Task: Implement User Authentication

### Phase 1: Data Layer
- Create User model with Prisma schema
- Write migration
- Run tests: `npm test -- --grep "User model"`
- Criteria: Model tests pass

### Phase 2: Service Layer
- Implement AuthService with JWT
- Add token generation/validation
- Run tests: `npm test -- --grep "AuthService"`
- Criteria: Service tests pass

### Phase 3: API Layer
- Create /auth/login endpoint
- Create /auth/register endpoint
- Run tests: `npm test -- --grep "auth API"`
- Criteria: API tests pass

### Phase 4: Integration
- End-to-end authentication flow
- Run tests: `npm test`
- Criteria: ALL tests pass

Output <promise>AUTH_COMPLETE</promise> when Phase 4 passes.

Step 3: Implement Safety Mechanisms

Always include escape conditions:

## Safety Rules

1. **Max Iterations**: Stop after 20 attempts
2. **Stuck Detection**: After 5 iterations without progress:
   - Document what's blocking
   - List attempted approaches
   - Suggest alternative strategies
3. **Critical Errors**: Stop immediately if:
   - Database corruption detected
   - Security vulnerability introduced
   - Breaking changes to existing features

Step 4: Execute with Verification

Each iteration should:

  1. Make targeted changes
  2. Run verification (tests, lint, build)
  3. Analyze results
  4. Plan next iteration based on feedback
# Iteration pattern
1. Read previous state (files, git log)
2. Identify remaining work
3. Implement specific change
4. Run verification suite
5. If all pass -> output completion promise
6. If failures -> analyze and continue iteration

Iterative Patterns

Pattern 1: Test-Driven Iteration

## TDD Iteration Task

1. Write failing test for [feature]
2. Implement minimal code to pass test
3. Run `npm test`
4. If test fails -> debug and fix implementation
5. If test passes -> check if more tests needed
6. Repeat until all acceptance tests pass
7. Refactor if needed
8. Output <promise>TDD_COMPLETE</promise>

Pattern 2: Bug Fix Iteration

## Bug Fix Task

1. Write failing test that reproduces bug
2. Implement fix
3. Run test suite
4. If reproduction test fails -> analyze why fix didn't work
5. If other tests fail -> fix regressions
6. If all tests pass -> output <promise>BUG_FIXED</promise>

Max iterations: 10
After 5 iterations without fix:
- Document root cause analysis
- Suggest alternative approaches

Pattern 3: Coverage Improvement Iteration

## Coverage Improvement Task

Target: 80% line coverage

1. Run coverage analysis
2. Identify uncovered code paths
3. Write test for highest-impact uncovered path
4. Run tests with coverage
5. If coverage >= 80% -> output <promise>COVERAGE_ACHIEVED</promise>
6. If coverage < 80% -> continue iteration

Max iterations: 30
Progress check: If coverage doesn't improve for 3 iterations -> analyze blockers

Pattern 4: Performance Optimization Iteration

## Performance Optimization Task

Target: Response time < 100ms

1. Run performance benchmark
2. Identify slowest operation
3. Implement optimization
4. Run benchmark again
5. If target met -> output <promise>PERF_TARGET_MET</promise>
6. If not improved -> try different approach

Max iterations: 15
Record metrics each iteration for trend analysis

Integration with Claude Flow

Memory-Enhanced Iteration

# Store iteration state
npx --no-install ruflo memory store \
  --key "current-iteration" \
  --value '{"task": "auth", "iteration": 5, "lastResult": "2 tests failing"}' \
  --namespace iterations

# Search for similar past iterations
npx --no-install ruflo memory search \
  --query "auth implementation" \
  --namespace iterations

# Learn from successful completions
npx --no-install ruflo hooks post-task \
  --taskId "auth-impl" \
  --success true \
  --quality 0.9

Swarm-Coordinated Iteration

For complex tasks, use multiple agents iterating in parallel:

# Initialize swarm for parallel iteration
npx --no-install ruflo swarm init --topology mesh --max-agents 5

# Spawn specialized iterators
Task("Iterate on unit tests", "Fix failing unit tests until all pass", "tester")
Task("Iterate on integration", "Fix integration tests until all pass", "tester")
Task("Iterate on performance", "Optimize until benchmarks pass", "performance-engineer")

Best Practices

Prompt Engineering for Iteration

Include:

  • Explicit completion criteria with verification commands
  • Phase-based breakdown for complex tasks
  • Safety limits (max iterations)
  • Progress tracking instructions
  • Stuck detection and recovery procedures

Example Well-Structured Prompt:

## Task: Implement Feature X

### Success Criteria (ALL must pass):
1. `npm test` exits with code 0
2. `npm run lint` exits with code 0
3. `npm run typecheck` exits with code 0
4. No console.log statements in production code

### Phases:
1. Write failing tests
2. Implement feature
3. Fix any failures
4. Clean up and refactor

### Safety:
- Max iterations: 20
- After 10 iterations: summarize blockers
- Stop if security issues detected

### Completion:
When ALL success criteria pass, output:
<promise>FEATURE_X_COMPLETE</promise>

When to Use Iterative Loops

Ideal for:

  • Well-defined tasks with measurable success
  • Test-driven development
  • Bug fixing with reproducible tests
  • Coverage improvement
  • Performance optimization
  • Linting/formatting fixes

Not ideal for:

  • Tasks requiring human judgment
  • Design decisions
  • Vague or subjective goals
  • One-time operations
  • Production debugging without tests

Troubleshooting

Issue: Infinite Loop / No Progress

Symptoms: Same errors repeat without improvement

Solutions:

  1. Increase specificity in completion criteria
  2. Add "stuck detection" with alternative approaches
  3. Lower max iterations
  4. Break task into smaller phases

Issue: False Completion

Symptoms: Loop ends but task not actually complete

Solutions:

  1. Add more verification commands
  2. Make completion criteria more explicit
  3. Add integration tests alongside unit tests

Issue: Regression in Later Iterations

Symptoms: Previously passing tests fail after new changes

Solutions:

  1. Add regression check step
  2. Use git to compare iterations
  3. Implement smaller, targeted changes

Related Skills

Resources


Origin: Based on Ralph Wiggum plugin from claude-code repository (anthropics/claude-code) Adapted for: Agentic QE v3 with Claude Flow integration

平台分布

Claude Code

28.01%
按下载量换算24

windsurf

22.98%
按下载量换算20

trae

17.23%
按下载量换算15

OpenCode

12.33%
按下载量换算11

Codex

7.17%
按下载量换算6

Antigravity

3.95%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill iterative-loop;npx skills add proffesor-for-testing/agentic-qe --skill "iterative-loop" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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