React Component Performance

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/react-component-performance

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

React Component Performance

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Checklist, Optimization Patterns, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• When the user asks to profile or improve a slow React component.
• When you need to reduce re-renders, list lag, or expensive render work in React UI.
• Use when the request clearly matches the imported source intent: Diagnose slow React components and suggest targeted performance fixes.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.

Operating Table

metadata.json

ORIGIN.md

references/examples.md

agents/openai.yaml

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Reproduce or describe the slowdown.
2. Identify what triggers re-renders (state updates, props churn, effects).
3. Isolate fast-changing state from heavy subtrees.
4. Stabilize props and handlers; memoize where it pays off.
5. Reduce expensive work (computation, DOM size, list length).
6. Validate: open React DevTools Profiler → record the interaction → inspect the Flamegraph for components rendering longer than ~16 ms → compare against a pre-optimization baseline recording.
7. Open React DevTools → Profiler tab.

Imported Workflow Notes

Imported: Workflow

1. Reproduce or describe the slowdown.
2. Identify what triggers re-renders (state updates, props churn, effects).
3. Isolate fast-changing state from heavy subtrees.
4. Stabilize props and handlers; memoize where it pays off.
5. Reduce expensive work (computation, DOM size, list length).
6. Validate: open React DevTools Profiler → record the interaction → inspect the Flamegraph for components rendering longer than ~16 ms → compare against a pre-optimization baseline recording.

Imported: Profiling Validation Steps

1. Open React DevTools → Profiler tab.
2. Click Record, perform the slow interaction, then Stop.
3. Switch to Flamegraph view; any bar labeled with a component and time > ~16 ms is a candidate.
4. Use Ranked chart to sort by self render time and target the top offenders.
5. Apply one optimization at a time, re-record, and compare render counts and durations against the baseline.

Imported: Overview

Identify render hotspots, isolate expensive updates, and apply targeted optimizations without changing UI behavior.

Imported: Checklist

• Measure: use React DevTools Profiler or log renders; capture baseline.
• Find churn: identify state updated on a timer, scroll, input, or animation.
• Split: move ticking state into a child; keep heavy lists static.
• Memoize: wrap leaf rows with

  memo

  only when props are stable.
• Stabilize props: use

  useCallback

  /

  useMemo

  for handlers and derived values.
• Avoid derived work in render: precompute, or compute inside memoized helpers.
• Control list size: window/virtualize long lists; avoid rendering hidden items.
• Keys: ensure stable keys; avoid index when order can change.
• Effects: verify dependency arrays; avoid effects that re-run on every render.
• Style/layout: watch for expensive layout thrash or large Markdown/diff renders.

Examples

Example 1: Ask for the upstream workflow directly

Use @react-component-performance to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @react-component-performance against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @react-component-performance for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @react-component-performance using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Example Reference

Load

references/examples.md

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/react-component-performance

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @prompt-engineer

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @prompt-engineering

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @prompt-engineering-patterns

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @prompt-library

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/examples.md

examples

examples/n/a

scripts

scripts/n/a

agents

agents/openai.yaml

assets

assets/n/a

• examples.md
• openai.yaml
• openai.yaml
• examples.md

Imported Reference Notes

Imported: Optimization Patterns

Isolate ticking state

Move a timer or animation counter into a child so the parent list never re-renders on each tick.

// ❌ Before – entire parent (and list) re-renders every second
function Dashboard({ items }: { items: Item[] }) {
  const [tick, setTick] = useState(0);
  useEffect(() => {
    const id = setInterval(() => setTick(t => t + 1), 1000);
    return () => clearInterval(id);
  }, []);
  return (
    <>
      <Clock tick={tick} />
      <ExpensiveList items={items} /> {/* re-renders every second */}
    </>
  );
}

// ✅ After – only <Clock> re-renders; list is untouched
function Clock() {
  const [tick, setTick] = useState(0);
  useEffect(() => {
    const id = setInterval(() => setTick(t => t + 1), 1000);
    return () => clearInterval(id);
  }, []);
  return <span>{tick}s</span>;
}

function Dashboard({ items }: { items: Item[] }) {
  return (
    <>
      <Clock />
      <ExpensiveList items={items} />
    </>
  );
}

Stabilize callbacks with

useCallback

+

memo

// ❌ Before – new handler reference on every render busts Row memo
function List({ items }: { items: Item[] }) {
  const handleClick = (id: string) => console.log(id); // new ref each render
  return items.map(item => <Row key={item.id} item={item} onClick={handleClick} />);
}

// ✅ After – stable handler; Row only re-renders when its own item changes
const Row = memo(({ item, onClick }: RowProps) => (
  <li onClick={() => onClick(item.id)}>{item.name}</li>
));

function List({ items }: { items: Item[] }) {
  const handleClick = useCallback((id: string) => console.log(id), []);
  return items.map(item => <Row key={item.id} item={item} onClick={handleClick} />);
}

Prefer derived data outside render

// ❌ Before – recomputes on every render
function Summary({ orders }: { orders: Order[] }) {
  const total = orders.reduce((sum, o) => sum + o.amount, 0); // runs every render
  return <p>Total: {total}</p>;
}

// ✅ After – recomputes only when orders changes
function Summary({ orders }: { orders: Order[] }) {
  const total = useMemo(() => orders.reduce((sum, o) => sum + o.amount, 0), [orders]);
  return <p>Total: {total}</p>;
}

Additional patterns

• Split rows: extract list rows into memoized components with narrow props.
• Defer heavy rendering: lazy-render or collapse expensive content until expanded.

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.