- slow page loads
- poor LCP, FCP, INP, CLS, TTFB, or TBT
- layout shifts and unstable rendering
- slow interactions caused by main-thread work
- image, font, or code-splitting regressions
Why This Skill?
Most frontend performance work fails because teams optimize without enough evidence or fix symptoms before upstream bottlenecks. This skill gives AI a repeatable workflow:- Collect the minimum useful evidence
- Identify the primary bottleneck
- Pick the matching optimization branch
- Re-measure when possible before claiming success
- MCP-assisted mode when Lighthouse or browser performance tooling is available
- Manual-evidence mode when you only have reports, traces, screenshots, or metric snapshots
Install
| Flag | Description |
|---|---|
-g | Install globally (~/.claude/skills/) |
-a claude-code | Target a specific agent |
-y | Non-interactive mode |
Verify Installation
Check if the skill is available:frontend-fullchain-optimization in the response.
Usage
After installation, ask AI to analyze the current performance evidence:What It Covers
| Area | Included guidance |
|---|---|
| Metrics | LCP, FCP, INP, CLS, TTFB, and TBT thresholds and prioritization |
| Diagnosis | Primary bottleneck decision tree and required evidence checklist |
| Optimization | Rendering, images, fonts, code splitting, layout stability, and interaction responsiveness |
| Verification | Before/after template for documenting improvements and remaining bottlenecks |
What’s Included
| File | Contents |
|---|---|
SKILL.md | The full performance workflow, metric playbooks, evidence checklist, and verification template |