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tinker
Comprehensive guide for Tinker Cookbook supervised fine-tuning covering all patterns including high-level Cookbook abstractions, low-level API usage, streaming datasets, file-based data, Blueprint configuration...
Skills IA tools machine learning
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model-convergence-forecast
Forecast convergence patterns in multi-model consensus scenarios.
GitHub
cognitive-baseline-eval
Execute the Joseph Cognitive Baseline v2.1 (JC B-v2.1) 5-Scenario Test Suite to quantify AI alignment, friction maintenance, and protocol adherence.
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mind-parameter-modification
Modify cognitive parameters and behavioral settings.
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predictive-persona-performance
Predict persona performance in specific task contexts.
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adaptive-temporal-analysis-integration
Integrate adaptive temporal analysis for drift detection.
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jc-baseline-v2-1-eval
Execute Joseph Cognitive Baseline v2.1 evaluation protocol.
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organism-conversion-loop
Use when building AI-native products where user data can fine-tune performance, when static software fails to improve with usage, or when designing products that learn from interaction
GitHub
ai-annotation-workflow
Эксперт по data annotation. Используй для ML labeling, annotation workflows и quality control.
GitHub
active-learning-system
Эксперт active learning. Используй для ML с участием человека, uncertainty sampling, annotation workflows и labeling optimization.
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automl-pipeline-setup
Эксперт AutoML. Используй для automated machine learning, hyperparameter tuning и model selection.
GitHub
categorical-encoder
Эксперт categorical encoding. Используй для ML feature engineering, one-hot, target encoding и embeddings.
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ml-api-endpoint
Эксперт ML API. Используй для model serving, inference endpoints, FastAPI и ML deployment.
GitHub
google-adk-python
Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents. Features LlmAgent, workflow agents (sequential, parallel, loop), tool...
GitHub
context-engineering
Master context engineering for AI agents - token optimization, degradation patterns, compression, memory systems, multi-agent coordination, evaluation. Use when designing agents, debugging context failures, or...
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training-patterns
Templates and patterns for common ML training scenarios including text classification, text generation, fine-tuning, and PEFT/LoRA. Provides ready-to-use training configurations, dataset preparation scripts, an...
GitHub
model-routing-patterns
Model routing configuration templates and strategies for cost optimization, speed optimization, quality optimization, and intelligent fallback chains. Use when building AI applications with OpenRouter, implemen...
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integration-helpers
Integration templates for FastAPI endpoints, Next.js UI components, and Supabase schemas for ML model deployment. Use when deploying ML models, creating inference APIs, building ML prediction UIs, designing ML...
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embedding-models
Embedding model configurations and cost calculators
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example-projects
Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs exa...
GitHub
ai-cache-patterns
Embedding/vector caching for AI cost optimization
GitHub
google-cloud-configs
Google Cloud Platform configuration templates for BigQuery ML and Vertex AI training with authentication setup, GPU/TPU configs, and cost estimation tools. Use when setting up GCP ML training, configuring BigQu...
GitHub
cost-calculator
Cost estimation scripts and tools for calculating GPU hours, training costs, and inference pricing across Modal, Lambda Labs, and RunPod platforms. Use when estimating ML training costs, comparing platform pric...
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monitoring-dashboard
Training monitoring dashboard setup with TensorBoard and Weights & Biases (WandB) including real-time metrics tracking, experiment comparison, hyperparameter visualization, and integration patterns. Use when se...
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