clustering-analyzer
Cluster data using K-Means, DBSCAN, hierarchical clustering. Use for customer segmentation, pattern discovery, or data grouping.
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Cluster data using K-Means, DBSCAN, hierarchical clustering. Use for customer segmentation, pattern discovery, or data grouping.
Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.
Create photo collages with grid layouts, custom arrangements, borders, and backgrounds. Combine multiple images into single compositions.
Extract vendor, date, items, amounts, and total from receipt images using OCR and pattern matching with structured JSON output.
This skill should be used when the user wants sequential AI-to-AI collaboration where one model drives and another reviews iteratively. Applies when the user wants to "collaborate with codex", "have c…
Comprehensive cognitive mode management skill for the VERILINGUA x VERIX x DSPy x GlobalMOO integration. Enables automatic mode selection, frame configuration, VERIX epistemic notation, and GlobalMOO …
End-to-end AI system evaluation - model selection, benchmarks, cost/latency analysis, build vs buy decisions. Use when selecting models, designing eval pipelines, or making architecture decisions.
Collecting and using user feedback - explicit/implicit signals, feedback analysis, improvement loops, A/B testing. Use when improving AI systems, understanding user satisfaction, or iterating on quali…
Extract dominant colors from images, generate color palettes, and export as CSS, JSON, or ASE with K-means clustering.
Detect language of text with confidence scores, support for 50+ languages, and batch text classification.
Generate organizational hierarchy charts from CSV, JSON, or nested data. Supports multiple layouts, department coloring, and PNG/SVG/PDF export.
Generate audio tones, noise, DTMF signals, and simple sound effects programmatically. Export to WAV or MP3 format.
Create DESIGN.md summaries from Google Stitch projects or offline assets for UI design workflows, and refine Stitch-ready UI prompts using extracted design tokens.
Ralph Wiggum persistence loop with intelligent multi-model routing (Gemini, Codex, Claude, Council)
Protecting AI applications - input/output guards, toxicity detection, PII protection, injection defense, constitutional AI. Use when securing AI systems, preventing misuse, or ensuring compliance.
ML framework best practices for PyTorch, TensorFlow, scikit-learn, and modern ML libraries including training patterns and optimization.
Extract contact information from business card images using OCR - name, company, email, phone, address.
Explain ML model predictions using SHAP values, feature importance, and decision paths with visualizations.
Split audio files by detecting silence gaps. Auto-segment podcasts into chapters, remove long silences, and export individual clips.
Detect quality drops in AI output and prompt re-anchoring. Auto-triggers after repeated corrections, context confusion, or when user says "something seems off", "you're not getting this".
Build high-quality MCP (Model Context Protocol) servers: workflow-first tool design, tight schemas, predictable outputs, safe error handling, and eval-driven iteration. Framework-agnostic (Node/TS or …
Use Gemini CLI for research with Google Search grounding and 1M token context
Optimizing AI inference - quantization, speculative decoding, KV cache, batching, caching strategies. Use when reducing latency, lowering costs, or scaling AI serving.
Core ML systems concepts including ML lifecycle, system architecture, requirements, and design principles for production ML.