benchmark-optimization-loop
Convert 'make it faster' requests into a bounded measured optimization loop — baseline first, generate one-hypothesis variants, benchmark each against a correctness gate, and promote the fastest safe variant with reproducible commands. Use when asked to speed something up, try many variants, run recursive optimization, benchmark latency/throughput/cost, or pick the best implementation by repeated measured tests.
Quellinformationen
- Repository
- affaan-m/ECC
- Letzte Quellaktivität
- 27. September 2026 um 20:46
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 269.367
- Forks
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- benchmark-optimization-loop
- description
- Convert 'make it faster' requests into a bounded measured optimization loop — baseline first, generate one-hypothesis variants, benchmark each against a correctness gate, and promote the fastest safe variant with reproducible commands. Use when asked to speed something up, try many variants, run recursive optimization, benchmark latency/throughput/cost, or pick the best implementation by repeated measured tests.
- license
- MIT
- metadata
- {"origin":"ECC"}
- tools
- Read, Write, Edit, Bash, Grep, Glob
# 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
1. Measure the baseline.
2. Identify bottlenecks from evidence.
3. Generate variants that test one hypothesis each.
4. Run variants with the same input shape.
5. Reject variants that fail correctness, safety, or reproducibility.
6. Promote the fastest safe variant.
7. Codify the winning path in a script, command, test, config, or doc.
8. Rerun the baseline and winner to confirm the delta.
## Variant Table
Track variants like this:
```text
Variant | Hypothesis | Command | Time | Correct? | Notes
baseline | current path | npm run job | 120s | yes | stable
batch-500 | fewer round trips | npm run job -- --batch 500 | 42s | yes | winner
parallel-8 | more workers | npm run job -- --workers 8 | 31s | no | rate limited
```
## Recursive Search
For recursive or hyperparameter work:
- persist every run to a ledger;
- compare against the prior accepted winner, not only the previous run;
- keep a holdout or replay check;
- stop when improvement is within noise, correctness fails, cost exceeds the
budget, or the search starts changing more variables than it can explain.
Use phrases like "best measured safe variant" instead of "global optimum" unless
the search space was actually exhaustive.
## Promotion Gate
A variant cannot become the new default until:
- correctness tests pass;
- the performance delta is repeated or explained;
- rollback is obvious;
- the change is encoded in source control or a durable runbook;
- the final summary includes exact commands and measurements.
Auf GitHub ansehen