alexbramall/claude-code-skills/run

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Run a single experiment iteration. Edit the target file, evaluate, keep or discard.

Install

npx vskill@latest install alexbramall/claude-code-skills/run

SKILL.md

The same SKILL.md was published earlier as agisota/old-one/run.

/ar:run — Single Experiment Iteration

Run exactly ONE experiment iteration: review history, decide a change, edit, commit, evaluate.

Usage

/ar:run engineering/api-speed # Run one iteration
/ar:run # List experiments, let user pick

What It Does

Step 1: Resolve experiment

If no experiment specified, run python {skill_path}/scripts/setup_experiment.py --list and ask the user to pick.

Step 2: Load context
bash
# Read experiment config
cat .autoresearch/{domain}/{name}/config.cfg
# Read strategy and constraints
cat .autoresearch/{domain}/{name}/program.md
# Read experiment history
cat .autoresearch/{domain}/{name}/results.tsv
# Checkout the experiment branch
git checkout autoresearch/{domain}/{name}
Step 3: Decide what to try

Review results.tsv:

  • What changes were kept? What pattern do they share?
  • What was discarded? Avoid repeating those approaches.
  • What crashed? Understand why.
  • How many runs so far? (Escalate strategy accordingly)

Strategy escalation:

  • Runs 1-5: Low-hanging fruit (obvious improvements)
  • Runs 6-15: Systematic exploration (vary one parameter)
  • Runs 16-30: Structural changes (algorithm swaps)
  • Runs 30+: Radical experiments (completely different approaches)
Step 4: Make ONE change

Edit only the target file specified in config.cfg. Change one thing. Keep it simple.

Step 5: Commit and evaluate
bash
git add {target}
git commit -m "experiment: {short description of what changed}"
python {skill_path}/scripts/run_experiment.py \
--experiment {domain}/{name} --single
Step 6: Report result

Read the script output. Tell the user:

  • KEEP: "Improvement! {metric}: {value} ({delta} from previous best)"
  • DISCARD: "No improvement. {metric}: {value} vs best {best}. Reverted."
  • CRASH: "Evaluation failed: {reason}. Reverted."
Step 7: Self-improvement check

After every 10th experiment (check results.tsv line count), update the Strategy section of program.md with patterns learned.

Rules

  • ONE change per iteration. Don't change 5 things at once.
  • NEVER modify the evaluator (evaluate.py). It's ground truth.
  • Simplicity wins. Equal performance with simpler code is an improvement.
  • No new dependencies.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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