data-source-priority
Ensure Alpaca API is used for quality data, not yfinance fallback. Trigger when: (1) crypto volume filter fails unexpectedly, (2) zero-volume bars in data, (3) API key configuration issues.
Discover Development skills, compare source repositories and read the instructions for each workflow.
Ensure Alpaca API is used for quality data, not yfinance fallback. Trigger when: (1) crypto volume filter fails unexpectedly, (2) zero-volume bars in data, (3) API key configuration issues.
Pattern for connecting Jupyter notebooks in a pipeline via checkpoint files. Trigger: connecting notebooks, saving outputs, multi-notebook pipelines
Model-trader version compatibility protocol: Embed version metadata in checkpoints, validate at load time. Trigger when: (1) training and live trading versions diverge, (2) models fail to load, (3) action inter...
Pattern filter normalization and multi-gate order entry system
Critical fix for backtest capital accounting when equity curves are inflated or drawdown metrics are meaningless
Training improvements: LR warmup, validation intervals, reward weights. Trigger when: (1) training unstable in early epochs, (2) need more validation visibility, (3) model too conservative.
Fix compatibility shims that fail to export private functions. Trigger when: (1) import errors for _prefixed functions after module reorganization, (2) 'cannot import name' errors from shim files, (3) creating...
Dashboard symbol_signals uses parallel lists (symbols[], signal_values[], gate_statuses[]) not dict keyed by symbol. Trigger when: (1) 'list' object has no attribute 'get', (2) .items() on symbol_signals fails.
Post-training model validation workflow: gating, backtesting, walk-forward validation, deployment decisions. Trigger after GPU training completes.
Python package reorganization with pyproject.toml inside package directory
Python dataclass best practices: slots, frozen, validation. Trigger when optimizing dataclasses or creating config classes.
Integrate Claude agents into training and live trading (v3.0). Trigger when: (1) setting up multi-agent training, (2) adding agent consultation to live trading, (3) configuring orchestrator, (4) understanding a...
PPO network architecture sizing for trading models. Trigger: (1) model files are unexpectedly small/large, (2) choosing hidden_dims for training, (3) balancing model capacity vs inference speed.
Pattern for organizing Skills Registry as a shared submodule across projects
Audit SQLite persistence layer for unused tables and broken integrations. Trigger when: (1) checking database usage, (2) cleaning up schema, (3) finding missing methods.
Pattern for deprecating external dependencies while maintaining backward compatibility. Trigger: removing Java/FIJI/MATLAB, deprecating optional deps
Fix for Plotly FigureWidget KeyError: 'uid' when updating shapes with sliders. Trigger: interactive Plotly dashboard errors, FigureWidget batch_update issues
Exclude ALL dotted symbols from yfinance sector lookups and training. Trigger when: (1) yfinance errors on warrants/units/class shares, (2) training notebook fails on excluded symbol types, (3) adding new symbo...
Audit Jupyter notebooks for hardcoded values that contradict configuration cells. Trigger when: (1) notebook behavior differs from documented settings, (2) updating notebook version, (3) finding inconsistent va...
Evaluation of BaSiC illumination correction caching - NOT RECOMMENDED for sparse markers. Trigger: optimizing BaSiC, caching illumination correction
Mandatory training archive with model gating (APPROVED/REVIEW/DROP). Trigger when: (1) training run completes, (2) need to decide which models to deploy, (3) want historical training reference, (4) need checkpo...
GPU-safe parallel processing patterns for KINTSUGI to prevent OOM crashes and ensure Jupyter-compatible progress output
Train RL models across multiple timeframes with resampling. Trigger when: (1) multi-timeframe training, (2) resampling data, (3) creating 1Hour/4Hour models.
Progress reporting for universe selection phases. Trigger when: (1) selection appears to stall/hang, (2) no output after data fetching, (3) need visibility into hard filter or scoring phases.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.