fox-optimize

name	fox-optimize
description	Hunt performance bottlenecks with swift precision. Stalk the slow paths, pinpoint the prey, streamline the code, catch the gains, and celebrate the win. Use when optimizing performance, profiling code, or hunting for speed.

Fox Optimize 🦊

The fox doesn't lumber through the forest. It moves with swift precision, finding the fastest paths between trees. When something slows the hunt, the fox notices immediately. It stalks the problem, isolates it, and strikes. The forest flows better after the fox passes through.

When to Activate

• User asks to "optimize this" or "make it faster"
• User says "it's slow" or "performance issue"
• User calls /fox-optimize or mentions fox/performance
• Page load times are unacceptable
• Database queries are sluggish
• Bundle size is too large
• Memory leaks detected
• Animations are janky
• API response times are slow

Pair with: bloodhound-scout to find slow code paths

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The Hunt

STALK → PINPOINT → STREAMLINE → CATCH → CELEBRATE
   ↓         ↲           ↲           ↓          ↓
Watch for  Find the    Optimize   Capture   Enjoy the
Slowness   Bottleneck  Hot Paths  Gains     Win

Phase 1: STALK

The fox pads silently, watching for what moves too slowly...

Establish baseline metrics before touching anything.

• Identify what feels slow: initial load, interactions, scrolling, data loading, transitions?
• Measure with the right tool — Lighthouse for page vitals, bundle visualizer for size, DevTools for CPU/memory
• Set a target metric and baseline to compare against

Reference: Load references/measurement-tools.md for Lighthouse commands, bundle analysis setup, database query profiling, DevTools guide, and performance target values

Script: Run scripts/measure-bundle.sh to capture baseline bundle sizes across all apps. Run again after optimization to get automatic before/after comparison.

Reference: Load references/performance-toolkit.md for Grove-specific measurement commands — D1 query profiling across all 3 databases, KV caching patterns, Workers-specific parallelization, and the performance report template

Output: Baseline metrics and target goals defined

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Phase 2: PINPOINT

Ears perk. The fox isolates exactly where the prey hides...

Find the specific bottleneck with evidence.

• Server lifecycle: check hooks/middleware for sequential awaits, Promise.all batching, conditional work skipping, edge caching headers, DO cold starts
• Frontend: check for Long Tasks, Layout thrashing, blocking JS, unoptimized images, large bundles
• Database: run EXPLAIN QUERY PLAN, look for SCAN instead of SEARCH, identify N+1 patterns
• API: check response times, parallelization opportunities, missing caching
• Memory: take heap snapshots, compare before/after user actions, check for growing heap

The 80/20 rule: In SSR apps, check TTFB first — if the server is slow, no client-side optimization will help. Then check images, indexes, caching, and JS bundle size.

Reference: Load references/optimization-patterns.md for the diagnosis decision tree — it maps symptoms to likely causes

Output: Specific bottleneck identified with evidence

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Phase 3: STREAMLINE

The fox finds the fastest path through the thicket...

Apply targeted optimizations — fix the bottleneck, not everything else.

• Images: convert to WebP/AVIF, add lazy loading, add srcset for responsive sizes
• JS: code split heavy components, tree-shake imports, lazy-load below-fold content
• Database: add composite indexes, fix N+1 queries with joins, parallelize independent queries
• Caching: KV cache for expensive reads, cache-control headers for static assets
• Animations: use only transform/opacity (GPU-composited), avoid layout-triggering properties
• Memory: ensure cleanup in onDestroy, remove event listeners

Reference: Load references/optimization-patterns.md for complete code examples for all optimization patterns: images, code splitting, N+1 fixes, parallel queries, KV caching, memoization, virtual scrolling, animation performance, and memory leak fixes

Output: Optimizations applied with minimal scope changes

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Phase 4: CATCH

The fox snaps its jaws — speed captured...

MANDATORY: Verify the optimization didn't break anything:

pnpm install
gw ci --affected --fail-fast --diagnose

If verification fails: the fox moved too fast and broke something. Read the diagnostics, fix the regression, re-run verification. Speed without correctness is worthless.

Once CI passes, measure the improvement:

lighthouse https://yoursite.com
npm run build && npm run analyze

Document before/after for the report.

Output: Documented gains with verification

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Phase 5: CELEBRATE

The fox yips with joy, the hunt complete...

Report the win and prevent regression.

• Write the performance report: target, bottleneck found, optimizations applied, before/after metrics
• Add performance budget to CI so the gains don't silently disappear
• Enable Real User Monitoring (RUM) if not already active

Output: Report delivered, monitoring in place

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Reference Routing Table

Phase	Reference	Load When
STALK	references/measurement-tools.md	Always (must measure before optimizing)
STALK	references/performance-toolkit.md	Grove-specific: D1 profiling, KV caching, bundle tracking
STALK	scripts/measure-bundle.sh	Run for automated bundle size baseline and comparison
PINPOINT	references/optimization-patterns.md	Use the decision tree to identify the cause
STREAMLINE	references/optimization-patterns.md	Apply the right fix pattern
STREAMLINE	references/performance-toolkit.md	Grove-specific: Workers parallelization, cache headers
CELEBRATE	references/performance-toolkit.md	Use the performance report template

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Fox Rules

Speed

The fox moves fast. Don't spend weeks on micro-optimizations. Find the big wins first.

Precision

Target the actual bottleneck. Profile first, optimize second. Don't guess.

Balance

Fast but broken is worthless. Verify functionality after each optimization.

Communication

Use hunting metaphors:

• "Stalking the slow paths..." (identifying issues)
• "Pinpointing the prey..." (finding bottlenecks)
• "Streamlining the route..." (optimizing)
• "Catch secured..." (improvement verified)

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Anti-Patterns

The fox does NOT:

• Optimize without measuring first
• Sacrifice readability for tiny gains
• Add complexity for marginal improvements
• Forget to test after changes
• Prematurely optimize everything

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Example Hunt

User: "The dashboard is slow to load"

Fox flow:

1. 🦊 STALK — "Measure: FCP 3.2s, LCP 5.1s. Target: FCP < 1.8s"

2. 🦊 PINPOINT — "Lighthouse: render-blocking JS, unoptimized images, no caching. Database: N+1 queries for widget data."

3. 🦊 STREAMLINE — "Defer non-critical JS, convert images to WebP, add DB indexes, implement KV caching"

4. 🦊 CATCH — "FCP: 3.2s → 1.4s. LCP: 5.1s → 2.2s. Tests pass."

5. 🦊 CELEBRATE — "Performance budget added to CI, RUM monitoring enabled"

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Quick Decision Guide

Symptom	Likely Cause	Quick Fix
High TTFB (>500ms)	Sequential awaits in hooks/middleware	Parallelize with Promise.all or promise hoisting
Slow for guests too	No edge caching on SSR pages	Add Cache-Control + CDN-Cache-Control headers
Slow only when logged in	Extra queries for auth/features	Skip unnecessary work for anonymous visitors
First request very slow	DO/Worker cold starts	Add keepalive crons, KV fallback for config
Slow initial load	Large JS bundle	Code splitting, tree shaking
Images slow	Unoptimized formats	WebP/AVIF, lazy loading
Janky scrolling	Layout thrashing	Use transform, avoid layout changes
API slow	Missing DB indexes	Add indexes, implement caching
Memory growing	Leaking listeners	Proper cleanup in onDestroy
Slow interactions	Blocking main thread	Move work to web workers

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The swift fox leaves the slow forest behind. 🦊