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webperf-resourcesWebperf 资源

Agent Skill

webperf-resources 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

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OpenClaw

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

MIT-0

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:webperf-resources(Webperf 资源)
来源仓库:https://github.com/nucliweb/webperf-resources
安装命令:
openclaw skills install webperf-resources
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 webperf-resources

简介

webperf-resources 用于智能网络质量分析,检测连接类型和带宽。

  • 自适应加载策略根据 2g/3g/4g、RTT 和数据节省模式调整资源加载。
  • 优化网络资源分配,提升弱网环境下的用户体验。
  • 安装命令为 openclaw skills install webperf-resources,需确认网络权限。
  • 建议结合来源仓库 README 核验具体用法,注意是否会触发命令执行或文件读写。

SKILL.md

name
webperf-resources
description
Intelligent network quality analysis with adaptive loading strategies. Detects connection type (2g/3g/4g), bandwidth, RTT, and save-data mode, then automatically triggers appropriate optimization workflows. Includes decision trees that recommend image compression for slow connections, critical CSS inlining for high RTT, and save-data optimizations (disable autoplay, reduce quality). Features connection-aware performance budgets (500KB for 2g, 1.5MB for 3g, 3MB for 4g+) and adaptive loading implementation guides. Cross-skill integration with Loading (TTFB impact), Media (responsive images), and Core Web Vitals (connection impact on LCP/INP). Use when the user asks about slow connections, mobile optimization, save-data support, or adaptive loading strategies. Compatible with Chrome DevTools MCP.
license
MIT
metadata
author
Joan Leon | @nucliweb
version
1.0.0
mcp-server
chrome-devtools
category
web-performance
repository
https://github.com/nucliweb/webperf-snippets

WebPerf: Resources & Network

JavaScript snippets for measuring web performance in Chrome DevTools. Execute with mcp__chrome-devtools__evaluate_script, capture output with mcp__chrome-devtools__get_console_message.

Scripts

  • scripts/Network-Bandwidth-Connection-Quality.js — Network Bandwidth & Connection Quality

Descriptions and thresholds: references/snippets.md

Common Workflows

Network Quality Assessment

When the user asks about network performance, connection quality, or adaptive loading:

  1. Network-Bandwidth-Connection-Quality.js - Analyze network bandwidth, effective connection type, RTT, downlink, save-data mode

Adaptive Loading Strategy

When implementing adaptive loading or the user asks "how to optimize for slow connections":

  1. Network-Bandwidth-Connection-Quality.js - Detect connection quality
  2. Cross-reference with webperf-loading skill:

- TTFB.js (measure server response on slow connections) - Find-render-blocking-resources.js (identify heavy resources to defer) - Resource-Hints-Validation.js (optimize preconnect for slow networks)

  1. Cross-reference with webperf-media skill:

- Image-Element-Audit.js (implement responsive images based on connection) - Video-Element-Audit.js (adjust video quality based on connection)

Save-Data Mode Detection

When the user asks about save-data or data-saving features:

  1. Network-Bandwidth-Connection-Quality.js - Check if save-data is enabled
  2. If save-data is enabled, recommend:

- Reducing image quality - Disabling autoplay videos - Deferring non-critical resources - Using low-res thumbnails

Mobile/Slow Connection Optimization

When the user asks "optimize for mobile" or "slow connection users":

  1. Network-Bandwidth-Connection-Quality.js - Assess connection type
  2. Cross-reference with webperf-loading skill:

- TTFB.js (critical for slow connections) - Find-render-blocking-resources.js (minimize blocking on slow networks) - Critical-CSS-Detection.js (inline critical CSS to reduce RTT) - Prefetch-Resource-Validation.js (avoid excessive prefetch on slow connections)

Decision Tree

Use this decision tree to automatically run follow-up snippets based on results:

After Network-Bandwidth-Connection-Quality.js

  • If effectiveType is "slow-2g" or "2g" → Very slow connection, recommend:

1. Run webperf-loading:Critical-CSS-Detection.js (inline critical CSS) 2. Run webperf-media:Image-Element-Audit.js (implement aggressive lazy loading) 3. Run webperf-loading:Prefetch-Resource-Validation.js (remove prefetch to save bandwidth) 4. Recommend minimal resource strategy

  • If effectiveType is "3g" → Moderate connection, recommend:

1. Run webperf-loading:Find-render-blocking-resources.js (minimize blocking) 2. Run webperf-media:Image-Element-Audit.js (responsive images) 3. Run webperf-loading:Resource-Hints-Validation.js (optimize preconnect) 4. Implement adaptive image quality

  • If effectiveType is "4g" or better → Good connection, recommend:

1. Standard optimization practices 2. Consider strategic prefetch for navigation 3. Higher quality media is acceptable

  • If save-data is enabled → User explicitly wants to save data, recommend:

1. Reduce image quality aggressively 2. Disable autoplay videos 3. Defer non-critical resources 4. Remove prefetch/preload hints 5. Show "high quality" toggle option

  • If RTT > 300ms → High latency, recommend:

1. Run webperf-loading:TTFB.js (latency impacts TTFB) 2. Run webperf-loading:Resource-Hints-Validation.js (preconnect critical for high RTT) 3. Minimize number of origins 4. Use HTTP/2 or HTTP/3 for multiplexing

  • If downlink < 1 Mbps → Very limited bandwidth, recommend:

1. Run webperf-media:Image-Element-Audit.js (aggressive compression) 2. Run webperf-media:Video-Element-Audit.js (disable autoplay) 3. Run webperf-loading:Prefetch-Resource-Validation.js (remove prefetch) 4. Implement bandwidth-aware loading

  • If downlink > 10 Mbps → Good bandwidth, consider:

- Higher quality media - Strategic prefetch - Preloading next-page resources

Cross-Skill Triggers

These triggers recommend using snippets from other skills:

From Resources to Loading Skill

  • If slow connection detected (2g/3g) → Use webperf-loading skill:

- TTFB.js (latency is amplified on slow connections) - Critical-CSS-Detection.js (reduce RTT by inlining critical CSS) - Find-render-blocking-resources.js (minimize blocking resources) - Resource-Hints-Validation.js (preconnect is critical for high RTT) - Prefetch-Resource-Validation.js (avoid prefetch on slow connections)

  • If high RTT detected (>200ms) → Use webperf-loading skill:

- TTFB-Sub-Parts.js (break down latency components) - Resource-Hints-Validation.js (preconnect to reduce RTT impact) - Service-Worker-Analysis.js (caching is critical for high latency)

From Resources to Media Skill

  • If slow connection or save-data detected → Use webperf-media skill:

- Image-Element-Audit.js (implement responsive images, aggressive compression) - Video-Element-Audit.js (disable autoplay, reduce quality)

From Resources to Core Web Vitals Skill

  • If slow connection detected → Check Core Web Vitals impact:

- Use webperf-core-web-vitals:LCP.js (LCP is heavily impacted by slow connections) - Use webperf-core-web-vitals:INP.js (high latency can impact interaction responsiveness)

Adaptive Loading Implementation Guide

Based on Network Information API results, implement these strategies:

For slow-2g / 2g (< 50 Kbps):

// Detected by effectiveType: "slow-2g" or "2g"
Strategies:
- Serve low-res images (quality: 30-40)
- Disable autoplay videos
- Remove all prefetch hints
- Inline all critical CSS
- Defer all non-critical JavaScript
- Use system fonts (no webfonts)
- Aggressive lazy loading (load on scroll + buffer)

For 3g (50-700 Kbps):

// Detected by effectiveType: "3g"
Strategies:
- Serve medium-res images (quality: 60-70)
- Disable autoplay videos
- Limited prefetch (critical only)
- Inline critical CSS only
- Defer non-critical JavaScript
- Preload 1-2 critical fonts
- Standard lazy loading

For 4g+ (> 700 Kbps):

// Detected by effectiveType: "4g"
Strategies:
- Serve high-res images (quality: 80-90)
- Allow autoplay videos (muted)
- Strategic prefetch for navigation
- Standard CSS loading
- Standard JavaScript loading
- Preload critical fonts
- Standard lazy loading

For save-data mode:

// Detected by navigator.connection.saveData === true
Strategies:
- Override connection type, treat as worse than actual
- Show "Load high quality" toggle
- Disable autoplay entirely
- Minimal images, minimal quality
- No prefetch, no preload (except critical)

Performance Budget by Connection Type

Adjust performance budgets based on connection quality:

slow-2g / 2g:

  • Total page weight: < 500KB
  • Images: < 200KB total
  • JavaScript: < 100KB total
  • No videos

3g:

  • Total page weight: < 1.5MB
  • Images: < 800KB total
  • JavaScript: < 300KB total
  • Videos: < 3MB (only if critical)

4g+:

  • Total page weight: < 3MB
  • Images: < 2MB total
  • JavaScript: < 1MB total
  • Videos: < 10MB

Real-World Scenarios

Scenario: User on 3G reports slow page load

  1. Run Network-Bandwidth-Connection-Quality.js → confirms 3g
  2. Run webperf-loading:TTFB.js → high TTFB due to latency
  3. Run webperf-loading:Critical-CSS-Detection.js → CSS not inlined
  4. Recommendation: Inline critical CSS, implement adaptive loading

Scenario: User with save-data enabled complains about data usage

  1. Run Network-Bandwidth-Connection-Quality.js → saveData: true
  2. Run webperf-media:Image-Element-Audit.js → high-res images served
  3. Run webperf-media:Video-Element-Audit.js → autoplay enabled
  4. Recommendation: Respect save-data, reduce quality, disable autoplay

Scenario: International users report slow LCP

  1. Run Network-Bandwidth-Connection-Quality.js → high RTT (300ms+)
  2. Run webperf-core-web-vitals:LCP.js → LCP 4s+
  3. Run webperf-loading:TTFB-Sub-Parts.js → DNS + connection = 500ms
  4. Recommendation: Use CDN, implement preconnect, optimize for latency

Scenario: Mobile users in rural areas

  1. Run Network-Bandwidth-Connection-Quality.js → 2g, high RTT, low downlink
  2. Run webperf-loading:Find-render-blocking-resources.js → many blocking
  3. Run webperf-media:Image-Element-Audit.js → all images eager-loaded
  4. Recommendation: Aggressive adaptive loading, inline critical CSS, lazy load all images

Network Information API Limitations

Be aware of API limitations and fallbacks:

API not available:

  • Safari does not support Network Information API
  • Fallback: Use TTFB as proxy for connection quality
  • Fallback: Device detection (mobile = assume slow)
  • Fallback: User preference toggle

API values are estimates:

  • effectiveType is based on recent observations
  • Values can change during session
  • Re-check periodically for long sessions

Privacy considerations:

  • Some browsers limit precision for privacy
  • Values may be rounded or capped
  • Consider user privacy when making decisions

Testing Adaptive Loading

To test adaptive loading implementations:

  1. Use Chrome DevTools Network Throttling
  2. Run Network-Bandwidth-Connection-Quality.js at each throttling level
  3. Verify adaptive strategies activate correctly
  4. Measure Core Web Vitals at each connection speed
  5. Adjust breakpoints and strategies based on results

Test matrix:

  • Offline
  • slow-2g (50 Kbps, RTT 2000ms)
  • 2g (250 Kbps, RTT 300ms)
  • 3g (750 Kbps, RTT 100ms)
  • 4g (4 Mbps, RTT 20ms)
  • save-data enabled at each level

References

  • references/snippets.md — Descriptions and thresholds for each script
  • references/schema.md — Return value schema for interpreting script output
Execute via mcp__chrome-devtools__evaluate_script → read with mcp__chrome-devtools__get_console_message.

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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。

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