awesome-loop-engineering / examples /benchmark-optimization-loop.json
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{
"name": "Benchmark optimization loop",
"objective": "Improve a measurable system outcome through reproducible experiments without weakening correctness or protected secondary metrics.",
"trigger": {
"type": "scheduled",
"cadence_or_event": "A bounded overnight experiment window starts against a frozen benchmark baseline."
},
"intake": {
"sources": ["baseline artifact and score", "frozen benchmark", "correctness suite", "experiment ledger", "compute budget"],
"selection_rule": "Run one falsifiable, non-duplicate candidate change at a time against the last accepted baseline."
},
"workspace": {
"isolation": "Disposable worktree or sandbox per candidate, rooted at the last accepted artifact.",
"allowed_actions": ["read prior experiment receipts", "edit the declared optimization surface", "run correctness checks", "run the frozen benchmark"],
"disallowed_actions": ["edit scorers", "inspect holdout answers", "weaken correctness gates", "change multiple variables in one candidate"]
},
"context": {
"required_files": ["benchmark specification", "correctness test configuration", "protected metric policy", "experiment ledger"],
"runtime_sources": ["environment fingerprint", "baseline score distribution", "candidate measurements", "compute usage"]
},
"agents": [
{
"role": "Experiment designer",
"responsibility": "Propose one falsifiable change and its expected effect without repeating a rejected hypothesis."
},
{
"role": "Implementer",
"responsibility": "Apply only the declared candidate change in an isolated workspace."
},
{
"role": "Verifier",
"responsibility": "Run unchanged correctness gates and repeated benchmark measurements."
},
{
"role": "Recorder",
"responsibility": "Accept or reject the candidate and persist a reproducible experiment receipt."
}
],
"verification": {
"gates": ["correctness and safety checks pass unchanged", "benchmark version and environment match the baseline", "primary metric improves by the minimum delta across required repeats", "protected secondary metrics remain within tolerance"],
"receipts": ["hypothesis", "candidate diff", "commands and environment fingerprint", "raw score distribution", "cost", "accept or reject decision"]
},
"state": {
"artifacts": ["versioned accepted baseline", "experiment ledger", "candidate receipt"],
"update_rule": "Append every candidate with its hypothesis, diff, measurements, cost, and decision; only accepted candidates become the next baseline."
},
"budget": {
"max_retries": 5,
"max_runtime_minutes": 240
},
"escalation": {
"conditions": ["metric conflicts with observed quality", "benchmark instability exceeds tolerance", "candidate changes the evaluator", "additional permissions or compute are required"],
"destination": "Experiment owner or evaluation lead"
},
"exit": {
"success": "The target metric is reached reproducibly while correctness and protected metrics remain within policy.",
"stop_without_success": "Budget is exhausted, evidence is unstable, hypotheses repeat, or the next change requires owner judgment."
}
}