Use when starting an ML task or choosing a method, to research papers/benchmarks and find the best approach and the REALISTIC accuracy ceiling. Finds SOTA, critically appraises reported numbers, and flags claims inflated by data leakage or ROI-cropping. Triggers on 'what's the best model/method for', 'state of the art', 'research papers', 'benchmark', 'how accurate can this get'.
How to install literature-review?
mxslr/mlcraft/literature-review
$npx -y skills add mxslr/mlcraft --skill literature-reviewInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/mxslr/mlcraft" --skill "mxslr/mlcraft/literature-review"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mxslr/mlcraft" that are relevant to the current task. Run `npx skills add "https://github.com/mxslr/mlcraft"` and select the relevant skills, then follow their instructions.
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