Leaf worker skill for ml-metaoptimization: analyzes experiment results against baselines and extracts learnings
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Updated
Apr 6, 2026
Leaf worker skill for ml-metaoptimization: analyzes experiment results against baselines and extracts learnings
Leaf worker skill for ml-metaoptimization: generates non-overlapping experiment proposals during the ideation phase
Leaf worker skill for ml-metaoptimization: implements experiment designs as code changes and patch artifacts
Leaf worker skill for ml-metaoptimization: designs concrete experiment batch specifications from winning proposals
Structured audit and remediation skill for Python, C, Rust, and assembly codebases — profiles structure, ranks a remediation backlog, and executes cleanup in verified batches
Leaf worker skill for ml-metaoptimization: ranks proposals and selects the winning experiment
Leaf worker skill for ml-metaoptimization: diagnoses failures during sanity checks and remote execution
Leaf worker skill for ml-metaoptimization: filters and curates the proposal pool during iteration rollover
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