Discover tools machine learning skills, compare source repositories and read the instructions for each workflow.
This skill should be used when refining hypotheses, checking testability, improving specificity, or designing verification strategies. Triggered by requests like "refine hypothesis", "validate hypothesis", "che...
Capture task outcomes, score performance, and derive rules as token priors for continual learning without model weight changes. Use for post-task feedback, experience capture, pattern extraction, and learning f...
Route tasks to small model by default, escalate to large model only on low confidence detection, achieving 87% faster learning and 10-30x cost reduction while maintaining accuracy. Use for cost optimization, co...
Tools for preparing and managing data for the PromptWar̊e ØS Vector Memory Subsystem.
Manage AI training data, monitor content freshness, detect repetition, and update training samples for continuous learning. Use when managing training data, checking content quality, updating AI models, or prev...
Guide for designing Instance resources in OptAIC. Use when creating DatasetInstance, SignalInstance, ExperimentInstance, ModelInstance, PortfolioOptimizerInstance, or BacktestInstance. Covers definition referen...
Follow these patterns when implementing quant domain resources like Dataset, Signal, Alpha, Portfolio, Strategy, Universe, Backtest, or MonitoringRun in OptAIC. Use for creating DB models, DTOs, services, and t...
Follow these patterns when implementing MLOps features in OptAIC. Use for ML model definitions (5-component structure), model instances, training/inference pipelines, model registry, and monitoring. Covers sign...
Follow these patterns when extending the OptAIC Python SDK with new domain operations. Use for adding client methods for datasets, signals, portfolios, backtests, and other resources. Covers async/sync interfac...
Cross-agent learning with cm (cass-memory). Use before starting non-trivial tasks, when looking for patterns from past work, when the user mentions "cm", "memory", "learned rules", or "what do we know about".
Advanced AI Solution Architect wisdom for designing production-grade AI systems. Use when (1) architecting new agents, workflows, or AI features, (2) debugging agent behavior or performance issues, (3) making t...
Feature development using DPPM framework (Discover, Plan, Prototype, Monitor). Use for feature planning and multi-agent orchestration.
Feature development using DPPM framework (Discover, Plan, Prototype, Monitor). Use for feature planning and multi-agent orchestration.
Consult other AI models via GitHub Copilot CLI for second opinions, thorough analysis, or alternative perspectives. Supports Gemini 3 Pro Preview (gemini), Claude Opus 4.5 (opus), Claude Sonnet 4.5 (sonnet) and...
Use this skill in the scenario of deep learning project development.
Develop and optimize AI prompt strategies for code generation. Use when creating new AI model strategies, optimizing prompts for Claude/GPT/Gemini/DeepSeek/Grok, or improving prompt quality. Includes model-spec...
Multi-stage deep investigation and reasoning for complex problems using PAL MCP. Use for architecture decisions, complex analysis, performance challenges, or when you need thorough reasoning. Triggers on comple...
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing...
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training a...
Design and refactor beam tracking ML/RL pipelines (CSI teacher vs RSRP student), enforce shape contracts, and produce inference-safe models.
Expert guidance for GabeDA v2.1 architecture (34 modules) - implementing models, features, debugging 4-case logic, and maintaining the /src codebase.
Choose the best Codex model (gpt-4 family, gpt-4o-mini, or legacy davinci) based on the workload described; use when the user asks for a model suggestion, wants to optimize quality vs cost/latency, or says “cha...
Guide for AI agent to use the tools offered by this library to perform analytic tasks.
GLM-4.7 모델을 효과적으로 활용하는 방법을 안내합니다. 사용자가 "GLM 사용법", "GLM 프롬프트", "GLM 최적화" 등을 질문할 때 활성화됩니다.
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.