Agent skill · Testing & QA

experiment-loop

Autonomous experiment loop: hypothesize > modify > test > evaluate > keep/discard > repeat. Run N experiments automatically with measurable metrics. Works for performance optimization, A/B testing, prompt engineering, and any measurable improvement task.

vibeevalgithub.com/vibeevalGitHub ↗
claude-codeMIT
Install
npx skills add vibeeval/vibecosystem --skill experiment-loop --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 7 KB
Bundled scripts: none
Path: skills/experiment-loop/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 521
Language: C#

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Experiment Loop Autonomous, iterative improvement inspired by Karpathy's autoresearch methodology. Define a metric, set a target, and let the loop run until the target is met or the iteration limit is reached. ## The 5-Step Loop ``` 1. HYPOTHESIZE -> Form a specific, falsifiable improvement hypothesis 2. MODIFY -> Apply the minimal code/config/prompt change 3. TEST -> Run the measurement suite (benchmarks, tests, evals) 4. EVALUATE -> Compare result against baseline and previous best 5. DECIDE -> KEEP if better, DISCARD (git stash pop --index) if worse | Repeat until target met OR max_iterations reached ``` Each iteration is atomic: one hypothesis, one change, one measurement, one decision. ## Experiment Definition Define an experiment in your task or in `thoughts/EXPERIMENTS.md`: ```yaml experiment: name: "reduce-api-latency" metric: "p95 response time (ms)" baseline: 340 target: 200 direction: minimize # minimize | maximize max_iterations: 10 # hard cap, never exceed measurement_cmd: "npm run bench:api" measurement_key: "p95" # JSON key from bench output scope: "src/api/" # files the loop is allowed to touch ``` ### Key Fields | Field | Description | |-------|-------------| | `

What's inside
Steps it walks through
  1. The 5-Step Loop
  2. Experiment Definition
  3. Key Fields
  4. Safety Protocol
  5. Agent Integration
  6. Example Experiments
  7. Bundle Size Reduction
  8. API Latency
  9. Test Coverage
  10. Prompt Engineering (LLM Eval)
  11. Results Log Format
  12. Iteration Limits and Exit Conditions
  13. Running the Loop
  14. Hard Limits
Commands it runs
Save current state
git stash push -u -m "experiment-loop: iteration N baseline"
Run experiment
Decision
if result is better:
git stash drop          # keep changes, discard stash
git stash pop --index   # restore exactly: staged + unstaged
More from vibecosystem
All skills →
About this skill
What does the experiment-loop skill do?

Autonomous experiment loop: hypothesize > modify > test > evaluate > keep/discard > repeat. Run N experiments automatically with measurable metrics. Works for performance optimization, A/B testing, prompt engineering, and any measurable improvement task.

How do I install it?

Run `npx skills add vibeeval/vibecosystem --skill experiment-loop --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 vibeeval/vibecosystem, a repository with 521 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.

Keep going