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Found 12 Skills
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.
Use when creating an R modeling package that needs standardized preprocessing for formula, data frame, matrix, and recipe interfaces. Covers: mold() for training data preprocessing, forge() for prediction data validation, blueprints, model constructors, spruce functions for output formatting.
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
Audit any eval, metric, experiment, or benchmark for leakage — does external ground-truth enter independently, or are the model, scorer, and designer just confirming a result no outside truth ever produced? Use before trusting any 'how we'll know it worked' — an A/B, a holdout, a score, a validation — and whenever a result feels too clean or self-confirming. Walks an 8-pattern leakage taxonomy and returns only the patterns that fire, each with an independence fix. Read-only.
Create and render OpenSCAD 3D models. Generate preview images from multiple angles, extract customizable parameters, validate syntax, and export STL files for 3D printing platforms like MakerWorld.
Cross Validation Setup - Auto-activating skill for ML Training. Triggers on: cross validation setup, cross validation setup Part of the ML Training skill category.
Guide for onboarding new model architectures into NeMo AutoModel, including architecture discovery, implementation patterns, registration, and validation.
Design computational models for cognitive simulation and analysis.
ASP.NET Core Web API implementation: clean controllers with CQRS, global error handling, model validation, Swagger/OpenAPI, API versioning, security (CORS, auth), middleware pipeline, and performance patterns. Use when creating or editing controllers, filters, middleware, Program.cs, or API endpoints.
Guides actuarial consulting engagements—client scoping and SOW design, stakeholder communication (CFO, risk, boards, regulators at overview level), due diligence and M&A actuarial support, reserving/pricing/capital review programs, model validation and opinion support, regulatory interaction prep, and deliverable governance (memos, exhibits, management presentations). Use when the user mentions actuarial consulting, actuarial engagement, reserve opinion, due diligence actuarial, model validation engagement, actuarial memo, SOW actuarial, regulatory actuarial, M&A reserves, or actuarial review—not deep technical modeling execution (actuary), P&C line education only (property-casualty-insurance), legal advice (commercial-counsel), or generic management consulting without actuarial lens (business-consultant).
Check BIM model consistency: naming conventions, parameter completeness, spatial relationships, and data integrity across model elements.
Use when designing Rails models - ActiveRecord patterns, validations, callbacks, scopes, associations, concerns, query objects, form objects