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AI-powered enterprise performance optimization orchestrator with Context7 integration, Scalene AI profiling, intelligent bottleneck detection, automated optimization strategies, and predictive perform…
AI-powered enterprise internal communications orchestrator with Context7 integration, intelligent content generation, automated workflow optimization, multi-format support (reports, newsletters, FAQs)…
Forecast convergence patterns in multi-model consensus scenarios.
Use this skill when coordinating multiple AI models (Claude, GPT, Gemini, DeepSeek) for competitive trading analysis, running parallel model execution, aggregating decisions, or managing model perform…
Select the best local Ollama model for a task and emit tuning presets. Use when choosing between reasoning, creative, fast, vision, synthesis, or pre-AGI modes based on available local models.
MONAD-grounded cognitive architecture for AI memory as morphemic substrate navigation. Memory is not storage but substrate sampling - accessing the same structure that underlies reality. Implements φ-…
Fast file editing via Morph Apply API (10,500 tokens/sec, 98% accuracy)
Generates a static MOVA AI bootstrap pack for a target model/environment (no LLM calls). Input: env.mova_ai_bootstrap_generate_v1, output: ds.mova_ai_bootstrap_pack_v1.
Enterprise EARS (Evaluate, Analyze, Recommend, Synthesize) Framework with AI-powered requirements engineering, Context7 integration, and intelligent solution orchestration for systematic problem-solvi…
Enterprise LLM Fine-Tuning with LoRA, QLoRA, and PEFT techniques
AI model configuration patterns for this project. Single source of truth for model definitions. Triggers on "MODEL_CONFIG", "model", "pricing", "capabilities", "auto router", "gateway".
Model-Development standards for model development in Ml Ai environments.
Control model behavior through persistent edits and steering interventions. Use when modifying model outputs, applying steering vectors, or creating persistently modified model versions.
MONAD-grounded cognitive architecture for AI memory as morphemic substrate navigation. Memory is not storage but substrate sampling - accessing the same structure that underlies reality. Implements φ-…
Expert guidance for building production-ready tool-calling agents with Databricks Mosaic AI Agent Framework. Use when users need to create agents that orchestrate multiple data sources or APIs, implem…
Design and orchestrate multi-agent AI systems with knowledge harvesting, agent collaboration, and learning loops. Use when working on PSI Engine or similar autonomous agent projects.
AI-powered enterprise refactoring with Context7 integration, automated code transformation, Rope pattern intelligence, and technical debt quantification across 25+ programming languages
Suggest MOC updates and new MOCs based on semantic clustering. Use when asked to "curate MOCs", "update maps", "find clusters", "what MOCs need updating", or "organize my notes".
Master Dyna-Q, MBPO, Dreamer - model-based RL with world models and planning
Model interpretability and explainability using SHAP, LIME, feature importance, and partial dependence plots. Activates for "explain model", "model interpretability", "SHAP", "LIME", "feature importan…
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
Moodle AI Subsystem integration for providers and actions. Use when integrating AI capabilities into Moodle, creating AI providers, or implementing AI actions.
Generates a static MOVA AI bootstrap pack for a target model/environment (no LLM calls). Input: env.mova_ai_bootstrap_generate_v1, output: ds.mova_ai_bootstrap_pack_v1.
Conduct comprehensive research on any topic by coordinating 2-4 specialized researcher agents in parallel, then synthesizing findings into a detailed report via mandatory report-writer agent delegatio…