mfowler 37032ee363 feat: campaign mode — repeat each variant N times, aggregate distributions
run-harness-bench.sh now loops VARIANTS × BENCH_REPEATS (default 5), writes each
run's row to RESULTS-campaign.md.data immediately (survives interruption), and
aggregates per-variant median/mean/min/max/stdev + median duration into
RESULTS-campaign.md. Frees each run's repo/transcripts after tallying.
2026-06-14 22:19:10 +00:00

agent-orchestrator-benchmark

Benchmarks for the agent-orchestrator harness — vendored here as the engine/ submodule, pinned at a ref that ships the example variants being compared.

What it measures

A head-to-head between two example variants in the engine:

  • builder-adversary — the original Builder/Adversary loop-pair prompts.
  • builder-adversary-min — the same pattern with the role + kickoff prompts compressed to minimal tokens.

The benchmark confirms each variant independently succeeds on the same task (no shared context) and clocks the tokens each uses.

Run

git submodule update --init      # fetch the vendored engine (first time)
./run-bench.sh                   # writes RESULTS.md

Needs claude on PATH and python/timeout. Both variants run on Sonnet (claude-sonnet-4-6) for Builder and Adversary.

How it works

run-bench.sh assembles exactly the prompt the harness would send a loop agent (the variant's kickoff.md with {phase_id}/{plan}/{status}/{role} substituted, then the role prompt), then drives one Builder pass and one Adversary pass as separate headless claude -p sessions — fresh context each, so the two variants (and the two roles) share no context. The Builder builds and commits in its own repo; the Adversary cold-verifies from its own clone. The script then re-runs the task's Definition-of-Done check itself and reads the Adversary's verdict, and tallies tokens from claude -p --output-format json.

The test problem is plans/roman.md — an integer→Roman-numeral CLI with a stdlib unittest suite (deterministic, fully local, cold-verifiable, and not present in either example).

Caveats

  • This is a controlled single pass per variant (N=1; expect run-to-run variance), not the full self-paced watchdog loop. It measures task effectiveness + prompt token cost, not the live loop / handoff / liveness machinery (that needs a real engine/agents.py up run).
  • Each claude -p call carries a fixed ~24k-token cached system-prompt/tool overhead, and most tokens come from the agentic work itself — so the prompt-size difference is a small slice of the total. RESULTS.md reports the static prompt size separately so the minimisation is visible.

Layout

engine/            agent-orchestrator, vendored as a submodule (the variants live in engine/examples/)
plans/roman.md     the test problem (single source of truth + Definition of Done)
run-bench.sh       the runner
RESULTS.md         generated by run-bench.sh
Description
Prompt token benchmarks for the agent-orchestrator harness (builder-adversary vs builder-adversary-min).
Readme 516 KiB
Languages
Python 95%
Shell 5%