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Product context: The modastack → bobi rename is a hard break (Zach, 2026-06-26). The legacy modastack CLI / .modastack
compatibility path was rejected — #530 and #531 are closed not-planned. This is the ...
Problem
The README currently exposes every workflow mode (Design, Build, Improve, Research, Clean PR, Meta) plus detailed
sections on the eval system, ACE self-improvement, and LangFuse tracing. This ...
1. Description
Train a logistic-regression classifier on flattened MNIST pixels. This is the subject s suggested first model: it
teaches how to turn images into a feature matrix and gives a non-deep baseline ...
model
phase-3.5-preliminary
是哪块业务逻辑:email-calendar m4 的 CalDAV 双向同步(intent#2「日历本地优先,CalDAV 双向同步 Radicale/Nextcloud/Apple/Fastmail」)。
暂定了什么:m4 已交付本地优先事件 CRUD + .ics 导入/导出(无依赖,round-trip 测过)+ 加密 CalDavAccount 模型。但真实 CalDAV 同步协议(PROPFIND/REPORT ...
vibehub-ticket
1. Description
The subject explicitly requires a preliminary warm-up: handle the MNIST digits dataset to learn how images work in
Python before the harder emotion problem. Here we just load MNIST, inspect ...
notebook
phase-3.5-preliminary
1. Description
One last look before modeling: inspect the exact tensors that will be fed to the network. Confirm shapes, dtypes, value
ranges, one-hot correctness, and that a few decoded samples still ...
notebook
phase-3-features
Mode: RUNTIME_MAINTENANCE_TASK Maintenance Task ID: publish_existing_issue_worktree Target Repository: alanua/Skeleton
Source Issue: 1122 Base Branch: main Output Branch: runner/issue-1122 Draft PR: true ...
memory
risk:yellow
runner:done
Product context: The modastack → bobi rename is a hard break (Zach, 2026-06-26). The legacy modastack CLI / .modastack
compatibility path was rejected — #530 and #531 are closed not-planned. This is the ...
1. Description
Turn the cleaned, split arrays into exactly what Keras expects: images shaped (N, 48, 48, 1), labels one-hot encoded to
(N, 7), wrapped in efficient tf.data.Dataset pipelines (batch, shuffle ...
data
phase-3-features
1. Description
Create the canonical data splits: respect FER-2013 s Usage column for the test set, and carve a stratified validation
set out of training. Fit every transform (standardization stats, PCA) ...
data
phase-3-features

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