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.
npx skills add vibeeval/vibecosystem --skill experiment-loop --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.
# 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 | |-------|-------------| | `
- The 5-Step Loop
- Experiment Definition
- Key Fields
- Safety Protocol
- Agent Integration
- Example Experiments
- Bundle Size Reduction
- API Latency
- Test Coverage
- Prompt Engineering (LLM Eval)
- Results Log Format
- Iteration Limits and Exit Conditions
- Running the Loop
- Hard Limits
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
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.
