profile-browsing

Profile Browsing Performance

Two-layer profiling: browser-level symptoms (Web Vitals, long tasks, scroll jank) and React-level diagnosis (commit counts, render bursts, per-component render data from react-scan). Each profiler subagent runs in its own browser session and context window.

Prerequisites

• Dev server running at https://seedit.localhost (yarn start via Portless)
• playwright-cli installed (npm install -g @playwright/cli@latest)

IMPORTANT: The orchestrator (you) is responsible for ensuring exactly ONE dev server is running. Profiler subagents must NEVER start a dev server themselves.

react-scan (already configured)

The app has react-scan set up in src/lib/react-scan.ts, imported in the entry file src/index.tsx. In dev mode it:

• Highlights rerendering components visually (toolbar + overlay)
• Tracks per-component render counts and times internally
• Exposes window.__getReactScanReport() for programmatic collection

The profiler's addInitScript sets window.__PROFILING__ = true before the app loads, which tells react-scan to disable its toolbar and sounds during automated runs.

No additional setup needed — react-scan is already a devDependency and imported in the entry file.

Step 0: Ensure Dev Server is Running

Before spawning any profiler subagents, verify exactly one dev server is available:

# Check if the dev server is reachable
curl -sf https://seedit.localhost -o /dev/null && echo "OK" || echo "NOT RUNNING"

• If OK: proceed to Step 1.
• If NOT RUNNING: start one instance with yarn start (backgrounded), then poll until it responds. Do NOT start more than one.
• If a dev server is already running on a different port (check ps aux | grep vite), reuse it — do not start another.

Step 1: Define Route Batches

Split routes into batches of 2–4 for parallel profiling.

Default batches (adjust boards as needed):

Keep batches balanced. Add thread views (/:boardIdentifier/thread/:cid) as needed.

Step 2: Spawn Profiler Subagents

Read the profiler subagent definition at .claude/agents/profiler.md. Then spawn one profiler Task per batch in parallel (single message, multiple Task calls):

For each batch, create a Task:
  subagent_type: "profiler"
  prompt: |
    Session name: "prof-N"
    Routes to profile: /route1, /route2, ...
    Any non-default app URL or extra profiling constraints

Spawn up to 4 subagents simultaneously. Each opens its own browser session, navigates routes, scrolls, collects both Web Vitals and react-scan data per route, and returns a structured issues list.

Trade-off: Parallel is faster but may skew timing results under heavy machine load. For precise measurements, spawn sequentially.

Step 3: Merge Results

Collect structured output from each subagent and merge:

1. Concatenate all Critical / Warning / React Rerenders / Scroll Jank / Info items
2. Combine per-view summary tables into one
3. Merge react-scan component data across routes (same component appearing in multiple routes = sum counts)
4. Deduplicate shared issues (e.g., same slow resource across routes)
5. Sort by severity (Critical first)

Step 4: Final Report

## Performance Profile Results

### Critical
- [metric]: [value] at [route] — [what likely needs fixing]

### Warning
- [metric]: [value] at [route] — [what likely needs fixing]

### React Rerenders
- [route]: [N] commits during load, [M] during scroll — [likely cause]
- Render bursts detected at [routes] — suggests cascading state updates
- Top rerendering components (react-scan):
  - [ComponentName]: [total count] renders across [routes], [time]ms total
  - [ComponentName]: [total count] renders across [routes], [time]ms total

### Scroll Jank
- [route]: [N] long tasks during scroll (max [X]ms), [M] React commits — [likely cause]

### Info
- [observations]

### Per-View Summary
| View | Nav (ms) | Long Tasks | CLS | LCP (ms) | Commits | Scroll Commits | Bursts | Top Component |
|------|----------|-----------|-----|-----------|---------|----------------|--------|---------------|
| /all | ... | ... | ... | ... | ... | ... | ... | ... |

Interpreting React Metrics

Element-source follow-up

When react-scan identifies a rerender hotspot but you still need the exact file behind a concrete DOM node, hand off to $inspect-elements.

playwright-cli -s=prof-followup eval "async el => JSON.stringify(await window.__ELEMENT_SOURCE__.resolve(el))" e7

Use source.filePath as the direct edit target and stack to understand which parent components own the node.

Step 5: Cleanup

After profiling is complete and the report is delivered, verify no orphaned processes were left behind:

# Check for any Vite dev servers started during profiling
ps aux | grep 'vite.*--port' | grep -v grep

• If the dev server was already running before Step 0, leave it alone.
• If the orchestrator started the dev server in Step 0, kill it now.
• If there are multiple Vite processes (should never happen), kill the extras and warn the user.

Also close any leftover playwright-cli sessions:

# Close any profiling sessions that weren't properly closed
playwright-cli -s=prof-1 close 2>/dev/null
playwright-cli -s=prof-2 close 2>/dev/null
playwright-cli -s=prof-3 close 2>/dev/null

Notes

• Session isolation: Each subagent uses a named playwright-cli session (-s=prof-N).
• Context isolation: Each subagent runs in its own context window.
• Per-route collection: Data resets on each goto — the profiler collects before navigating away.
• addInitScript persistence: Instrumentation re-injects automatically in each new document.
• Tracing: Each subagent produces a trace.zip viewable in Trace Viewer.
• Routes: communities are addressed directly as /s/<community-address>; /s/all aggregates the default communities.
• Without react-scan: If __getReactScanReport returns null, the profiler falls back to commit counts + render bursts (still useful, just no component names).