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beringresearch
Dimensionality reduction in very large datasets using Siamese Networks
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Dimensionality reduction in very large datasets using Siamese Networks
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This skill should be used for improving context efficiency: context budgeting, observation masking, prefix or KV-cache strategy, partitioning, token-cost reduction, retr…
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Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling,…
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Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment). Use when the user mentions "users arent coming back", "habit form…
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Expert patterns for simplifying 3D games to 2D including dimension reduction strategies, 2.5D fake-depth, isometric ports, camera flattening, physics conversion, 3D-to-s…
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Use when the user has a judge/grader and human-labeled data, and wants to measure how well the judge agrees with humans, detect systematic biases, determine whether auto…
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Reduction pass — cuts content, structure, visuals, and dead code that doesn't answer a user question or drive an action, respecting CRAFT_LEVEL. Use when the UI feels cl…
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Use this skill when the user needs to improve conversion rates, reduce funnel drop-off, optimize signup flows, or increase trial-to-paid conversion. Covers funnel analys…
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Inventing deterministic metrics — turning a fuzzy property like 'maintainability', 'risk', or 'how reducible this code is' into a deterministic, computable number an age…
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Optimizes API performance through payload reduction, caching strategies, and compression techniques. Use when improving API response times, reducing bandwidth usage, or…