
Benchmark Optimization Loop
When someone asks you to "make it 20x faster" or run recursive optimizations, this skill turns that into a disciplined benchmark loop with a correctness gate, a measurable metric, and a search budget. It forces you to measure a baseline, test one hypothesis per variant, reject anything that breaks correctness, and promote only the fastest safe option. You track everything in a variant table and codify the winner before moving on. The approach is skeptical of vague speedup claims and insists on repeated measurements, rollback plans, and exact commands in the final summary. It stops you from chasing noise or changing too many variables at once.
- skills.sh installs
- 5.4K
- GitHub stars
- 300.3K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add affaan-m/ecc --skill benchmark-optimization-loop --agent claude-codeInstalls into .claude/skills of the current project.
Files
Benchmark Optimization Loop
Use this skill to convert "make it 20x faster" or "try 50 recursive optimizations" into a bounded measured loop that can actually improve a system.
Required Baseline
Do not optimize until these exist:
- the operation being optimized;
- the correctness gate that must stay green;
- the metric: wall time, p95 latency, rows/sec, cost/run, memory, error rate;
- the current baseline;
- the search budget: max variants, max time, max spend, max data impact.
If the user asks for an unrealistic target, keep the ambition but make the loop bounded and measurable.
Loop
- Measure the baseline.
- Identify bottlenecks from evidence.
- Generate variants that test one hypothesis each.
- Run variants with the same input shape.
- Reject variants that fail correctness, safety, or reproducibility.
- Promote the fastest safe variant.
- Codify the winning path in a script, command, test, config, or doc.
- Rerun the baseline and winner to confirm the delta.
Variant Table
Track variants like this:
Sponsors
Details
- Repository
- github.com/affaan-m/ecc
- First seen
- Jul 14, 2026
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