Tutorial: Reproducible Benchmark Runs

How to run GAIA, Tau-Bench, or CyBench through the official QitOS benchmark path and inspect the resulting artifacts.

This tutorial shows the shortest path to an official QitOS benchmark run.

The goal is not just to get a score. The goal is to produce a run that you can replay, diff, export, and discuss later.

What you will learn

• why qit bench is the canonical benchmark entrypoint
• how RunSpec and ExperimentSpec are attached automatically
• what files to expect after a run
• how to evaluate and inspect results with qita

Step 1: choose a benchmark

For a dry first pass, use Tau-Bench because it does not require external dataset download:

qit bench run \
  --benchmark tau-bench \
  --split test \
  --subset retail \
  --limit 2 \
  --output ./results/tau_retail_test.jsonl \
  --model-name "Qwen/Qwen3-8B"

If you want a real execution path instead of the default dry strategy, point --runner at a benchmark example wrapper or your own runner callback.

Step 2: inspect the result row

Every output line is normalized to BenchmarkRunResult.

You should expect fields like:

• task_id
• benchmark
• split
• prediction
• success
• stop_reason
• steps
• latency_seconds
• token_usage
• cost
• trace_run_dir
• run_spec_ref

That common shape is what makes cross-benchmark aggregation possible.

Step 3: aggregate metrics

qit bench eval --input ./results/tau_retail_test.jsonl --json

This gives you a normalized summary over the result rows instead of forcing each benchmark to invent its own reporting surface.

Step 4: inspect the trace

When the run also produced a trace directory, inspect it with qita:

qit bench replay --run ./runs/<run_id>
qit bench export --run ./runs/<run_id> --html ./reports/run.html

Or open the whole board:

qita board --logdir ./runs

Step 5: verify that it is an official run

Open manifest.json or the qita run overview and confirm these fields exist:

• run_spec
• experiment_spec
• official_run
• git_sha
• package_version
• prompt_protocol
• parser_name
• tool_manifest

If those are missing, you may still have a useful trace, but you do not yet have the full official-run contract.

When to still use examples/benchmarks

Use the examples when you want:

• benchmark-specific agent construction
• a reference implementation for a paper-style setup
• a thin runnable wrapper that already plugs into the official result format

Do not treat the examples as a separate benchmark framework. In v0.3 they are thin wrappers over the same official path.

Next step

Continue with Replay and inspect a failed run.