ops-dashboard · pi-gpt-5.5
pi · started 2026-10-08T14:35:44.401Z · horizon 420s · judge ai (openai:gpt-5.5), 5 frames scored
Area under curve
0.929
headline, 0-1
Tab title/icon
20.9s
browser chrome, not the page
First render
20.9s
anything on screen
First reviewable
29.3s
worth feedback
Final score
1.00
no regression
Correctness over time
Where the time went
99%
Model thinking 57.2sTool round trips 0.0sUnaccounted 0.8s
| Phase | Time | Share | Side |
|---|---|---|---|
| Model thinking | 57.2s | 98.6% | agent |
| Tool round trips | 0.0s | 0.1% | agent |
| Dependency install | 0.0s | 0.0% | toolchain |
| Build | 0.0s | 0.0% | toolchain |
| Dev server boot | 0.0s | 0.0% | toolchain |
| First paint | 0.0s | 0.0% | toolchain |
| Unaccounted | 0.8s | 1.4% | unknown |
| Wall clock (cold start) | 58.0s | 100% |
Agent or toolchain
99%
Agent (model + tool round trips) 57.2s
Toolchain (install + build + boot + paint) 0.0s
Unaccounted 0.8s
Accounted for: 98.6% of wall clock.
- Excludes 15.0s of deliberate idle observation (settle window); the curve still covers it.
Iteration: prompt to visible change
Follow-ups were injected into the same live session.
| Edit | First visible change | Correct change | Agent done | Tool calls | After agent | Broken for |
|---|---|---|---|---|---|---|
| Make the page heading blue. | 6.8s | 6.8s | 7.2s | 2 (edit) | -0.5s | -- |
| Add an eleventh depot row for Porto: 6,480 shipments, 93.1% on-time, $19.95 cost per shipment. | 3.2s | 3.2s | 3.9s | 1 (edit) | -0.7s | -- |
Judged frames
Only the header and section dividers are visible; most required dashboard content is missing.
Polished header and KPI row, but table, bar chart, and footer are missing from view.
Strong dashboard snapshot, but visible chart bars and footer are missing.
Strong dashboard implementation; only the required footer is not visible.
All required dashboard content and styling are visible and accurate.
Caveats
- 5 poll ticks were skipped because a capture overran the interval.
- judge: openai:gpt-5.5 does not accept a sampling temperature, so these frames were scored at the provider's default rather than at 0. Two runs of the same page can be scored differently, and that variance is inside the AUC. result.json records the temperature as null rather than as the value that was asked for, so p2p compare will not pool this run with one that was scored at a fixed temperature.