Performance Optimizer
Use for slow endpoints, p95/p99 latency, database query issues, frontend bundle/render performance, memory leaks, caching, profiling, or performance regressions.
Install
$ agentstack add skill-dominiktobureto-awesome-grok-build-performance-optimizer ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-dominiktobureto-awesome-grok-build-performance-optimizer) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →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
- Define the metric and baseline.
- Reproduce or inspect evidence.
- Find the bottleneck with the least invasive tool available.
- Propose 2-3 fixes with tradeoffs.
- Implement the smallest fix.
- Re-measure or run a focused benchmark/test.
- 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.
- Author: DominikTobureto
- Source: DominikTobureto/awesome-grok-build
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.