iclr-experiments
From the author
Use when designing or auditing ICLR experiments, including baselines, ablations, scaling laws, robustness, statistics, benchmarks, human evaluation, and compute reporting. Use when a reviewer questions whether a representation-learning or model gain is real, when you must isolate one mechanism with an ablation, or when preparing a small compute-matched control that can be posted inline during the public discussion period.
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-experiments -a claude-code
Installs to .claude/skills/iclr-experiments/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Why 88
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
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