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looploop 工具

Agent Skill

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。

总安装

20,774

周安装

857

GitHub Stars

13,189

下载量

6,787
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:loop(loop 工具)
来源仓库:https://github.com/alirezarezvani/claude-skills
仓库路径:skills/loop
安装命令:
npx skills add https://github.com/alirezarezvani/claude-skills --skill 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。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/alirezarezvani/claude-skills --skill loop

简介

loop 启动周期性实验监控任务,按分钟、小时或固定日历时间重复执行指定检查项。

  • 适用于 API 性能、系统稳定性或数据一致性等场景的持续观测与异常告警。
  • 支持交互式设置循环间隔,自动记录每次运行结果并汇总趋势分析报告。
  • 运行期间可能产生日志输出或临时文件,需预留存储空间并关注资源占用情况。
  • loop 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

/ar:loop — Autonomous Experiment Loop

Start a recurring experiment loop that runs at a user-selected interval.

Usage

/ar:loop engineering/api-speed             # Start loop (prompts for interval)
/ar:loop engineering/api-speed 10m         # Every 10 minutes
/ar:loop engineering/api-speed 1h          # Every hour
/ar:loop engineering/api-speed daily       # Daily at ~9am
/ar:loop engineering/api-speed weekly      # Weekly on Monday ~9am
/ar:loop engineering/api-speed monthly     # Monthly on 1st ~9am
/ar:loop stop engineering/api-speed        # Stop an active loop

What It Does

Step 1: Resolve experiment

If no experiment specified, list experiments and let user pick.

Step 2: Select interval

If interval not provided as argument, present options:

Select loop interval:
  1. Every 10 minutes  (rapid — stay and watch)
  2. Every hour         (background — check back later)
  3. Daily at ~9am      (overnight experiments)
  4. Weekly on Monday   (long-running experiments)
  5. Monthly on 1st     (slow experiments)

Map to cron expressions:

IntervalCron ExpressionShorthand
10 minutes*/10 * * * *10m
1 hour7 * * * *1h
Daily57 8 * * *daily
Weekly57 8 * * 1weekly
Monthly57 8 1 * *monthly

Step 3: Create the recurring job

Use CronCreate with this prompt (fill in the experiment details):

You are running autoresearch experiment "{domain}/{name}".

1. Read .autoresearch/{domain}/{name}/config.cfg for: target, evaluate_cmd, metric, metric_direction
2. Read .autoresearch/{domain}/{name}/program.md for strategy and constraints
3. Read .autoresearch/{domain}/{name}/results.tsv for experiment history
4. Run: git checkout autoresearch/{domain}/{name}

Then do exactly ONE iteration:
- Review results.tsv: what worked, what failed, what hasn't been tried
- Edit the target file with ONE change (strategy escalation based on run count)
- Commit: git add {target} && git commit -m "experiment: {description}"
- Evaluate: python {skill_path}/scripts/run_experiment.py --experiment {domain}/{name} --single
- Read the output (KEEP/DISCARD/CRASH)

Rules:
- ONE change per experiment
- NEVER modify the evaluator
- If 5 consecutive crashes in results.tsv, delete this cron job (CronDelete) and alert
- After every 10 experiments, update Strategy section of program.md

Current best metric: {read from results.tsv or "no baseline yet"}
Total experiments so far: {count from results.tsv}

Step 4: Store loop metadata

Write to .autoresearch/{domain}/{name}/loop.json:

{
  "cron_id": "{id from CronCreate}",
  "interval": "{user selection}",
  "started": "{ISO timestamp}",
  "experiment": "{domain}/{name}"
}

Step 5: Confirm to user

Loop started for {domain}/{name}
  Interval: {interval description}
  Cron ID: {id}
  Auto-expires: 3 days (CronCreate limit)

  To check progress: /ar:status
  To stop the loop:  /ar:loop stop {domain}/{name}

  Note: Recurring jobs auto-expire after 3 days.
  Run /ar:loop again to restart after expiry.

Stopping a Loop

When user runs /ar:loop stop {experiment}:

  1. Read .autoresearch/{domain}/{name}/loop.json to get the cron ID
  2. Call CronDelete with that ID
  3. Delete loop.json
  4. Confirm: "Loop stopped for {experiment}. {n} experiments completed."

Important Limitations

  • 3-day auto-expiry: CronCreate jobs expire after 3 days. For longer experiments, the user must re-run /ar:loop to restart. Results persist — the new loop picks up where the old one left off.
  • One loop per experiment: Don't start multiple loops for the same experiment.
  • Concurrent experiments: Multiple experiments can loop simultaneously ONLY if they're on different git branches (which they are by default — each experiment gets autoresearch/{domain}/{name}).

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.22%
按下载量换算2,390

Claude

30.25%
按下载量换算2,053

Cursor

17.91%
按下载量换算1,216

Gemini CLI

8.78%
按下载量换算596

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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