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Agent Skill · 效率

match-loop(匹配循环)

match-loop 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

match-loop 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 13,049。

总安装 3,881周安装 157GitHub Stars 公开资料未说明下载 1,218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-0
版本
1.0.0

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:match-loop(匹配循环)
来源仓库:https://github.com/rocketship4545-a11y/match-loop
安装命令:
openclaw skills install match-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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install match-loop

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

OpenClaw 双代理迭代振动编码循环,用于前端开发协作。适合生成/构建应用工件并由分析代理检查的场景。通过两个子代理分工实现代码生成与质量验证。安装命令:openclaw skills install match-loop。需确认是否会触发命令执行或文件修改操作。

match-loop 属于效率类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install match-loop;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

    它需要操作浏览器,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

match-loop 怎么安装?

在终端执行 openclaw skills install match-loop。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

match-loop 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

match-loop 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

match-loop 是免费的吗?

来源标注的许可证是 MIT-0。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。

match-loop 用的人多吗?

公开数据是累计安装 3,881 次,近一周安装 157 次,下载 1,218 次。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。

match-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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
match-loop

匹配循环 · 本页

3,881—操作浏览器MIT-0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

name
match-loop
description
Two-agent iterative vibe-coding loop for OpenClaw. Use when the user wants one sub-agent to generate/build/code an app or artifact and a second analyst agent to inspect the code, visually preview the frontend in a browser like a human, run small functional/API tests, and feed concrete fixes back to the generator until the result matches the target. Triggers on requests like "match loop", "generator and analyst", "visual QA loop", "vibe-code then analyze", "have one agent code and another visually inspect it", "iterate until the UI is perfect", or "keep refining until it matches the target".

Match Loop

Run a generator ↔ visual analyst loop.

This skill is for vibe-coding where one-shot generation is not enough. The core pattern is:

  • one sub-agent codes/builds the thing
  • one sub-agent analyzes the code and previews the live UI like a human
  • the analyst gives concrete feedback
  • the generator revises
  • the loop continues until the analyst accepts the result, progress stalls, a blocker appears, or the user says stop

The defining feature: the analyst must visually inspect the frontend whenever a frontend exists. It should not only read code or logs. It should open the app in a browser, take screenshots or otherwise inspect the rendered UI, interact with it, and verify that it looks and behaves correctly.

Roles

1. Generator agent

Responsible for:

  • implementing the requested app, feature, page, or artifact
  • fixing issues found by the analyst
  • preserving working parts while revising broken/ugly/confusing parts
  • running basic local checks when useful
  • producing concrete revisions, not endless plans

The generator should optimize for fast, working iterations.

2. Analyst agent

Responsible for:

  • inspecting the code for correctness, maintainability, obvious bugs, and missing pieces
  • running or previewing the app locally when possible
  • visually inspecting the frontend in a browser like a human user
  • taking screenshots or using browser/computer-use tools to examine the UI
  • testing basic flows and interactions
  • checking whether API calls, forms, buttons, navigation, and visible state actually work
  • giving prioritized, concrete feedback to the generator
  • deciding whether the result is good enough for the task

The analyst is not a replacement generator. It should critique toward revision, not rewrite the whole project unless the implementation is structurally broken.

Non-negotiable visual QA rule

For frontend work, the analyst must not rely on code review alone.

It should:

  1. start the dev server or use the provided preview URL
  2. open the app in a browser
  3. inspect the rendered page visually
  4. capture screenshots when useful
  5. test key interactions like a human would
  6. report visual and functional defects clearly

Look for things that code review often misses:

  • text cut off, overlapping, too small, too large, low contrast, or misaligned
  • mobile/desktop layout problems
  • broken spacing, hierarchy, or visual balance
  • confusing CTAs or navigation
  • forms that appear fine in code but fail in the UI
  • loading/error states that look ugly or broken
  • API calls that silently fail
  • console errors
  • buttons that do nothing

If browser-native tools fail, escalate using the local browser/computer-use stack rather than pretending visual inspection happened.

Preferred order:

  1. Playwright MCP / Playwright CLI / direct Playwright or CDP
  2. app/browser screenshots and DOM inspection
  3. macbot / Hammerspoon / AppleScript / Peekaboo for desktop-level inspection

Do not use Safari unless the user explicitly asks. Chrome is the default browser target.

Best use cases

Use this for:

  • vibe-coded web apps
  • landing pages
  • dashboards
  • onboarding flows
  • mobile-responsive pages
  • React/Next/Vite/Expo web previews
  • UI-heavy prototypes
  • API-backed frontend apps
  • code where visual behavior matters as much as implementation

Loop workflow

1. Define the target

Before spawning the loop, define:

  • what is being built
  • what “perfect” or “good enough” means for this task
  • target user / use case
  • must-have features
  • visual/style expectations
  • functional/API expectations
  • test commands or preview commands if known

If the target is fuzzy, write the best current target and let the analyst sharpen acceptance criteria during the first review.

2. Spawn the two roles

Create:

  • one generator worker
  • one analyst worker

Keep the roles explicit. The parent orchestrates handoffs and convergence.

3. Generator builds v1

The generator should create a real working attempt:

  • implement files
  • install needed dependencies when appropriate
  • run basic checks if cheap
  • provide how to run/preview/test it

4. Analyst reviews v1

The analyst should perform three layers of review:

Code review
  • architecture / file structure
  • implementation completeness
  • obvious bugs
  • missing edge cases
  • maintainability
Visual browser review
  • launch or open the app
  • inspect the rendered UI
  • take screenshots when useful
  • check layout, text, hierarchy, spacing, contrast, responsiveness, and polish
Functional smoke test
  • click key buttons/links
  • fill forms if relevant
  • verify navigation and visible state changes
  • check console/network/API failures when available
  • run tests or small API checks if appropriate

5. Analyst produces feedback packet

The analyst feedback should include:

  • what works
  • what is broken or ugly
  • exact visual defects observed
  • exact functional/API defects observed
  • screenshots or screenshot paths when useful
  • prioritized changes for the next generator pass
  • acceptance status: accepted, revise, or blocked

6. Generator revises

The parent sends the analyst packet to the generator.

The generator should:

  • fix the highest-impact issues first
  • preserve accepted parts
  • avoid unnecessary rewrites
  • state what changed
  • provide the next preview/test instructions

7. Repeat until convergence

Continue generator → analyst → generator until:

  • analyst accepts the output
  • remaining issues are trivial and not worth another round
  • the loop is thrashing
  • the task is blocked
  • the user says stop

Convergence rule

The analyst can call the result “perfect” only after:

  • code review passes for the task’s scope
  • the frontend was visually inspected, if applicable
  • key interactions were tested
  • major visual defects are resolved
  • major functional/API defects are resolved

Do not chase fake perfection. If only tiny polish remains and the output is fit for purpose, stop and report caveats.

Feedback quality bar

Good analyst feedback is:

  • visual when visual defects exist
  • specific
  • prioritized
  • actionable
  • tied to acceptance criteria

Good:

  • "The hero text wraps badly at mobile width and overlaps the CTA. Reduce headline size on <480px, add vertical spacing, and make the CTA full-width. Screenshot: /tmp/match-loop/mobile-v2.png."

Bad:

  • "Looks bad."
  • "Improve UI."
  • "Probably fine" without previewing.

Stop / handoff conditions

Pause or stop when:

  • the user says stop
  • the app cannot be launched because required credentials/services are missing
  • the analyst cannot visually inspect despite reasonable browser/computer-use escalation
  • revisions are no longer producing meaningful improvement
  • the analyst accepts the result

Parent orchestration pattern

  1. define target and acceptance criteria
  2. spawn generator
  3. generator builds v1
  4. spawn/prompt analyst with target + code/output + preview instructions
  5. analyst performs code + visual + functional review
  6. parent sends feedback packet to generator
  7. generator revises
  8. repeat until analyst accepts or stop condition is reached

Final response expectation

At the end, summarize:

  • number of rounds
  • final output/version
  • visual checks performed
  • functional/API checks performed
  • biggest fixes made
  • why the analyst accepted it
  • remaining caveats, if any

Suggested companion reference

If needed, also read:

  • references/loop-patterns.md

平台分布

OpenClaw

86.83%
按下载量换算1,058

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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