bad-name
Name does not match its folder.
- License 许可
- MIT
- 最近更新
- 2026-10-25
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01 前言 Front Matter
- name
- bad-name
- description
- Name does not match its folder.
02 资源文件 35
- 资产文件assets/style-frame-spec.example.json1.4 KB
- 资产文件assets/templates.md2.8 KB
- 参考文档examples/brand-launch.md2.2 KB
- 参考文档examples/ui-iteration.md2.6 KB
- 参考文档references/01-idea-positioning.md2.0 KB
- 参考文档references/02-naming-brand.md2.6 KB
- 参考文档references/03-find-references.md3.8 KB
- 参考文档references/03b-style-names-and-creative-decode.md7.3 KB
- 参考文档references/03c-creative-derivation-method.md8.6 KB
- 参考文档references/03d-creative-operator-library-tutti-seed.md40.0 KB
- 参考文档references/04-style-bible.md2.1 KB
- 参考文档references/05-feature-planning.md3.4 KB
- 参考文档references/06-ui-build-loop.md3.6 KB
- 参考文档references/06b-visual-craft.md13.6 KB
- 参考文档references/06c-web-craft.md12.5 KB
- 参考文档references/07-asset-generation.md3.1 KB
- 参考文档references/08-device-qa.md3.8 KB
- 参考文档references/09-launch-video.md2.6 KB
- 参考文档references/10-gtm-social.md2.8 KB
- 参考文档references/11-growth-data.md1.8 KB
- 参考文档references/12-ship-opensource.md1.8 KB
- 参考文档references/12b-oss-distribution.md4.0 KB
- 参考文档references/13-trademark-ip.md2.1 KB
- 参考文档references/mistakes.md16.7 KB
- 参考文档references/user-repeated-demands.md16.7 KB
- 脚本scripts/appstore_refs.py2.5 KB
- 脚本scripts/cut.swift1.3 KB
- 脚本scripts/cutout_vector.sh2.2 KB
- 脚本scripts/domain_check.py4.7 KB
- 脚本scripts/gh_exposure.py3.3 KB
- 脚本scripts/phase_gate.py11.2 KB
- 脚本scripts/ref_archive.py3.0 KB
- 脚本scripts/ref_frames.py4.8 KB
- 脚本scripts/style_frame.py11.1 KB
- 脚本scripts/vectorize.js1.1 KB
03 SKILL.md 正文
Never loaded.
04 同仓库更多 Skills
tabular-demo
Demo step skill for tabular data.
leakage-demo
Demo knowledge skill about target leakage.
train-test-split
How to split data so the score is honest.
tabular-features
Writes src/features.py with derived features (ratios, logs, interactions) and no target use. Usually right after tabular-eda. Check: run src/features.py, expects data/processed/features.csv.
tabular-export
Writes the shipped code (src/pipeline.py, src/train.py, src/predict.py) from the winning run and trains it. Usually right after evolve-search or tabular-ensemble. Check: run src/train.py, expects models/model.joblib, metric accuracy (classification) or r2 (regression) with a minimum.
tabular-ensemble
Combines the search's top models into a stacking ensemble. Only when the top genomes are within about 1% of each other. Check: metric cv_score with a minimum.