Development skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

spf-implement-feature

Implement a feature documented in the SPF feature registry. Consumes a feature doc at internal/design/spf/features/<name>.md and produces the engine-side code: new behaviors, updates to existing behaviors, media-layer / network-layer primitives, and tests. The implementation analog of /spf-document-feature (which produces the doc; this consumes it). Walks through resolving the doc's open questions before coding, maps phases to discrete chunks, applies the SPF conventions catalog, routes to downstream skills (/spf-create-behavior, /spf-update-behavior, /refactor-behavior) per chunk shape, and updates the feature doc's Status / Implementation surface / Verification sections as code lands. Triggers: "implement feature", "implement SPF feature", "build feature", "code feature", "scope feature implementation", "implement <feature-name>".

868 repo starsObserved in 1 repos
Development
GitHub

spf-implement-use-case

Implement a use-case composition documented in the SPF use-case-composition registry. Consumes a use-case doc at internal/design/spf/use-cases/<name>.md and produces the engine-side code: a variant engine factory, a parallel adapter, composition wiring, use-case-specific behaviors (if any), and tests. The implementation analog of /spf-document-use-case (which produces the doc; this consumes it). Walks through disambiguation + routing (verify the request is actually a use case, check constituent-feature implementation status), resolves the doc's open questions with the user, maps phases to chunks, routes to downstream skills (/spf-implement-feature for unimplemented constituents, /spf-create-behavior, /spf-update-behavior, /refactor-behavior), and updates both the use-case doc and constituent feature docs as code lands. Treats the use-case doc as a starting point for planning, not a hardened specification. Triggers: "implement use case", "implement SPF use case", "implement use-case composition", "build use case", "implement audio-only-mode-override", "implement <use-case-name>".

868 repo starsObserved in 1 repos
Development
GitHub

spf-update-behavior

Update an existing SPF behavior whose purpose is changing or expanding. Distinct from /refactor-behavior, which preserves purpose — this skill handles cases where the behavior gains new responsibility (new state slot to react to, new lifecycle phase, new constraint, new code path). Carries /refactor-behavior's purpose-first discipline applied to the *purpose change*. Triggers: "update behavior", "extend behavior", "modify behavior", "change behavior purpose", "expand behavior responsibility".

868 repo starsObserved in 1 repos
Development
GitHub

split-behavior

Split one SPF behavior into N with axis-declared, constraints-audited discipline. Forces explicit axis declaration (per-type horizontal vs. per-concern vertical) and a cross-boundary constraint audit before the split lands — avoids the failure mode where an apparent per-type-friendly behavior ships a split that quietly drops a cross-type ordering invariant the merged code was enforcing. Use after /refactor-behavior's decomposition check has concluded "split," or when you've already noticed a behavior wants splitting. Triggers: "split this behavior", "split into per-type", "extract per-type behaviors", "convert to per-type variants", "split behavior".

868 repo starsObserved in 1 repos
Development
GitHub

marmite-development

Guidelines and workflows for contributing to the marmite codebase - covers code quality, testing, architecture patterns, and contribution checklists

867 repo starsObserved in 1 repos
Development
GitHub

code-science

Scientific programming best practices including reproducible research, computational notebooks, version control for research, data management, HPC/parallel computing, and research software engineering. Use when user needs help with research code organization, reproducibility, scientific Python/R workflows, or computational infrastructure. Triggers on "reproducible research", "research code", "scientific computing", "HPC", "parallel computing", "Jupyter", "notebook", "data management plan", "research software", "code review for science".

866 repo starsObserved in 3 repos
Development
GitHub

ml-pipeline

Machine learning pipeline for scientific research including data preprocessing, feature engineering, model selection, training, evaluation, and interpretation. Covers supervised/unsupervised learning, deep learning, cross-validation, hyperparameter tuning, and model explainability. Use when user asks to build a predictive model, classify data, cluster samples, do feature selection, or apply ML to research data. Triggers on "machine learning", "classification", "clustering", "random forest", "neural network", "deep learning", "predict", "feature selection", "cross-validation", "train model".

866 repo starsObserved in 3 repos
Development
GitHub

scientific-generation

Generate scientific code, protocols, and domain-specific text with quality control

866 repo starsObserved in 3 repos
Development
GitHub

scikit-learn-ml

Machine learning with scikit-learn. Use when: classification, regression, clustering, dimensionality reduction, model evaluation, feature engineering. NOT for: deep learning (use transformers/pytorch), time series forecasting (use statsmodels), big data (use spark).

866 repo starsObserved in 3 repos
Development
GitHub

f8-editor-assetmanager-workflow

Use when working with AssetManager editor tools — F8 shortcut, AB name management, asset index generation, and asset status inspector in F8Framework.

866 repo starsObserved in 2 repos
Development
GitHub