Agent Setup Scorecard
Compare three named agent setup patterns against the same dummy task suite, then read which setup to use and what still needs fixing before it touches a real workflow.
What this proves
A pass rate only helps when you know which agent setup produced it and what it fails on. The scorecard turns a fuzzy model choice into a named setup pattern, a failure row, and the next fix.
How it works
What This Proves
The I/O 2026 agent-eval talks gave the same warning twice: a 70% pass rate on one task suite tells you nothing about whether the workflow is ready. The shape of the misses matters more than the number.
This scorecard makes the shape visible. Three named setup patterns run the same bundled suite. The card surfaces the recommended setup, the weakest row, and the cheapest fix instead of leaving the reader with an abstract benchmark.
What This Build Does
- Loads a bundled task suite: research packet, ops CSV cleanup, or support triage
- Compares three implementation patterns: Browser Planner, Schema Runner, and Critic Loop
- Shows which setup is safest for that workflow and what needs to be fixed next
Safety Boundaries
- Deterministic only. The scorecard never invokes a real model or vendor API.
- No vendor claim. The setup names are generic implementation patterns, not product benchmarks.
- Sample task suites only. Suites are dummy data; the scorecard never implies a benchmark on a real workload.
What Would Come Next
- Add a side-by-side mode for two suites at once, such as research packet vs ops CSV cleanup
- Surface a per-task drilldown so the recommendation links to the failing row
- Export the scorecard as CSV so it lands cleanly in a PR description
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