ln-31-performance-optimizer
Optimizes a measured latency, throughput, memory, CPU, or I/O problem through profiling and keep-or-discard experiments. Use for a known bottleneck; not unbiased A/B comparison.
Profile →npx skills add levnikolaevich/claude-code-skills --skill ln-31-performance-optimizer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Performance Optimizer **Goal:** Optimize only measured problems. Preserve correctness, isolate experiments, and retain a change only when comparable evidence shows that it improves the agreed metric without unacceptable regressions. **Execution contract:** Treat the ordered checkbox workflow below as this skill's Definition of Done. Work through every item in order, and mark it complete only when its action and required evidence are complete. `N/A`, skipped, unavailable, or delegated items remain incomplete. Before returning, apply this skill's verdict, decision, and approval rules to every incomplete item and prepend **Checklist: X/Y complete**<br>**Incomplete: None | section/item — reason; outcome impact; exact next action**; list every incomplete item. ## Tool Routing | Need | Preferred tool | Use it when | Fallback | |---|---|---|---| | Repository state and safe edit boundary | Git status, diff, branch or worktree inspection, and repository instructions | Always before profiling or editing | Stop if user changes cannot be isolated safely | | Baseline and final metric | Existing benchmark, load test, reproducible command, or production-like replay | The metric and workload ref
- Tool Routing
- Evidence Rules
- Checklist
- 1. Define the Problem and Protect the Workspace
- 2. Establish a Reproducible Baseline
- 3. Profile and Form Hypotheses
- 4. Execute Atomic Keep-or-Discard Experiments
- 5. Stop, Verify, and Report
- Output Contract
What does the ln-31-performance-optimizer skill do?
Optimizes a measured latency, throughput, memory, CPU, or I/O problem through profiling and keep-or-discard experiments. Use for a known bottleneck; not unbiased A/B comparison.
How do I install it?
Run `npx skills add levnikolaevich/claude-code-skills --skill ln-31-performance-optimizer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From levnikolaevich/claude-code-skills, a repository with 528 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.