Web Performance Optimization
Evidence-led web performance — measure with real-user signals, diagnose with traces
- What
- Evidence-led web performance — measure with real-user signals, diagnose with traces
- Cost
- Free
- Needs
- none beyond a working agent; a runnable web page and a browser performance-trace tool (Chrome DevTools MCP recommended) for the evidence-led workflow
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — an evidence-led web performance methodology from the web-quality-skills collection: establish a field-plus-lab baseline before editing, prioritize poor real-user Core Web Vitals, diagnose with browser performance traces and focused insights (not Lighthouse's non-performance categories), change only the code connected to measured bottlenecks, and report before/after values with uncertainty. Includes starting performance budgets (page weight, JS/CSS, images, fonts, third-party) calibrated to target devices and networks, plus critical-rendering-path guidance (TTFB, compression, HTTP/2-3, edge caching). Distinct from the already-listed addyosmani-performance-optimization: different repository, different method — that one is Addy Osmani's general performance guidance; this one is the web-quality-skills team's measurement-first workflow with budgets and trace-based diagnosis. By @addyosmani, listed here with credit to its creator. Honest caveats: needs a runnable page and a browser trace tool (Chrome DevTools MCP recommended) to be fully evidence-led — without them, findings are hypotheses; field verification requires enough new user data. Skill Harbor never reviews the code, review it yourself before use.
Version:
Install
Prerequisites: none beyond a working agent; a runnable web page and a browser performance-trace tool (Chrome DevTools MCP recommended) for the evidence-led workflow Install "Web Performance Optimization" for me. Evidence-led web performance — measure with real-user signals, diagnose with traces Repository: https://github.com/addyosmani/web-quality-skills/blob/main/skills/performance/SKILL.md 1. Fetch the SKILL.md file for the addyosmani-performance skill from the repository into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "addyosmani-performance". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. any accounts, API keys, or CLI tools mentioned in the prerequisites above). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. Never ask me to paste secrets in chat — credentials go through the secure vault or environment variables. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.