performance-check

A CSS rule for replacing repeated style values with existing CSS variables, such as shared colors, spacing, or font sizes. CSS variables are named values reused across a stylesheet.

In plain words
What is it for?
Use it when optimizing CSS variable usage, especially to check unconverted values against the variables defined in styles.css.
Why use it?
It prevents inconsistent substitutions by allowing a value to be replaced only when an existing variable matches it exactly and has a suitable meaning.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/adobecom/da-express-milo/performance-check
Clone the repo
git clone --depth 1 https://github.com/adobecom/da-express-milo

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,095 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01095
Opus 5 $0.00000 $0.00548
Sonnet 5 $0.00000 $0.00219
Haiku 4.5 $0.00000 $0.00110

Measured 2d ago against content hash 9bb7af12a0fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

performance-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/build-block-from-figma/agents/performance-check.md · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Check Subagent

This script is delegated from Phase 7 of the main SKILL.md. Run only after the visual comparison loop (Phase 5) and the accessibility audit (Phase 6) are complete.


Target thresholds

The project maintains Lighthouse scores above 90. The block must not cause regressions.

Metric Target Why it matters
Overall score ≥ 90 Composite performance health
LCP (Largest Contentful Paint) ≤ 2.5 s Most important metric — measures perceived load speed
CLS (Cumulative Layout Shift) ≤ 0.1 Layout stability
INP (Interaction to Next Paint) ≤ 200 ms Responsiveness
TBT (Total Blocking Time) ≤ 200 ms Main-thread availability

Tool

Uses the lighthouse CLI (installed as a project dev dependency) executed via Playwright MCP's shell/terminal access.


Procedure

  1. Run Lighthouse against the Playwright URL in headless Chrome:
    npx lighthouse <playwright-url> \
      --output=json \
      --output-path=/tmp/lighthouse-report.json \
      --chrome-flags="--headless --no-sandbox" \
      --only-categories=performance
    
  2. Parse the JSON output and extract:
    • categories.performance.score (multiply by 100 for the percentage)
    • audits['largest-contentful-paint'].numericValue (LCP in ms)
    • audits['cumulative-layout-shift'].numericValue (CLS)
    • audits['total-blocking-time'].numericValue (TBT in ms)
    • audits['interaction-to-next-paint'].numericValue (INP in ms, if available — this may require user interaction to measure)
  3. Assess each metric against the target thresholds.

LCP-specific assessment

Since LCP is the most critical metric, perform additional analysis:

  1. Identify the LCP element from the Lighthouse report: audits['largest-contentful-paint'].details.
  2. Check if the LCP element is inside the new block.
    • If yes, the block directly impacts LCP. Assess whether the block's CSS or JS is delaying the LCP paint.
    • If no, the block is not the LCP bottleneck — but still verify it doesn't add blocking resources.
  3. Common LCP pitfalls in blocks:
    • JS that runs synchronously before the block's content is visible.
    • CSS that hides content on initial load and reveals it after a transition (e.g. opacity: 0opacity: 1 with a delay).
    • Large unoptimised images loaded eagerly above the fold.
    • Web fonts that block text rendering.

Read the full file on GitHub · 132 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 132 lines · 0 tokens per session scan A 9bb7af12a0fb

Subscribe to this mod's changes

performance-check is an agent published in the GitHub repository adobecom/da-express-milo (6 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,095 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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