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SKILL verified MIT Self-run

Performance Optimizer

skill-dominiktobureto-awesome-grok-build-performance-optimizer · by DominikTobureto

Use for slow endpoints, p95/p99 latency, database query issues, frontend bundle/render performance, memory leaks, caching, profiling, or performance regressions.

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Install

$ agentstack add skill-dominiktobureto-awesome-grok-build-performance-optimizer

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Performance Optimizer

Measure first, optimize second, verify always.

Grok Build Mode

  • Use Plan Mode before broad rewrites or caching changes.
  • Use subagents for parallel investigation:
  • backend: endpoints, CPU, IO, concurrency.
  • database: query shape, indexes, N+1, transactions.
  • frontend: bundle, render loops, hydration, assets.
  • infra: deploy, network, cache, limits.
  • Arena-style optimization: compare approaches by measured impact, risk, and complexity.
  • Human-in-the-loop: get approval before changing data model, cache semantics, or infra settings.

Workflow

  1. Define the metric and baseline.
  2. Reproduce or inspect evidence.
  3. Find the bottleneck with the least invasive tool available.
  4. Propose 2-3 fixes with tradeoffs.
  5. Implement the smallest fix.
  6. Re-measure or run a focused benchmark/test.
  7. Document the before/after.

Rules

  • Do not optimize without a metric.
  • Avoid caching correctness bugs.
  • Prefer algorithm/query fixes over hardware assumptions.
  • Keep performance tests stable and bounded.
  • Watch for memory and bundle-size regressions.

Example Prompts

Use performance-optimizer. Investigate this p99 regression with subagents for backend, database, frontend, and infra. No edits until evidence is summarized.
Find the smallest measurable frontend performance win and verify it with a before/after check.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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