Perf Theory Tester
- 63 installs
- 931 repo stars
- Updated July 26, 2026
- avifenesh/agentsys
perf-theory-tester is a skill that validates performance hypotheses via controlled single-change experiments.
About
perf-theory-tester validates performance hypotheses through controlled experiments. A developer uses it to confirm a clean baseline, apply one change tied to a hypothesis, run repeated validation passes, then revert before the next test. It records metric deltas and an accept, reject, or inconclusive verdict for each experiment.
- Validates a performance hypothesis with a single controlled change per experiment
- Runs 2+ validation passes and reverts to baseline before the next experiment
- Emits an accept/reject/inconclusive verdict with metric deltas and evidence
Perf Theory Tester by the numbers
- 63 all-time installs (skills.sh)
- Ranked #284 of 596 Debugging skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
perf-theory-tester capabilities & compatibility
- Capabilities
- perf experiment · benchmark runner · baseline comparison
- Use cases
- testing · debugging
- Pricing
- Free
What perf-theory-tester says it does
Test hypotheses using controlled experiments.
One change per experiment.
No parallel benchmarks.
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| Installs | 63 |
|---|---|
| repo stars | ★ 931 |
| Last updated | July 26, 2026 |
| Repository | avifenesh/agentsys ↗ |
What it does
Run controlled, single-change perf experiments to accept or reject a performance hypothesis.
Who is it for?
Confirming whether a single change improves a measured performance metric.
Skip if: Generating the hypotheses or running parallel benchmarks.
When should I use this skill?
When running controlled perf experiments to validate hypotheses.
What you get
A per-hypothesis verdict (accept/reject/inconclusive) with metric deltas and recorded evidence.
- experiment verdict with metric deltas and evidence
By the numbers
- 4 required steps
- 2+ validation passes
- one change per experiment
Files
perf-theory-tester
Test hypotheses using controlled experiments.
Follow docs/perf-requirements.md as the canonical contract.
Required Steps
1. Confirm baseline is clean. 2. Apply a single change tied to the hypothesis. 3. Run 2+ validation passes. 4. Revert to baseline before the next experiment.
Output Format
hypothesis: <id>
change: <summary>
delta: <metrics>
verdict: accept|reject|inconclusive
evidence:
- command: <benchmark command>
- files: <changed files>Constraints
- One change per experiment.
- No parallel benchmarks.
- Record evidence for each run.
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