By athola
Run local ONNX Runtime model inference via an HTTP daemon, with automatic provisioning of Python and ONNX Runtime using uv, and lifecycle management through session hooks.
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Intelligent delegation framework for routing tasks to external LLM services while retaining strategic oversight
Git and workspace operations for active development workflows - commit messages, PR prep, documentation updates, and version management
Reflective code review toolkit with structured analysis, blast radius analysis, domain expertise, and intelligent review orchestration
Codebase visualization — generates architecture, data flow, dependency, call chain, community detection, and class diagrams via Mermaid Chart MCP
Meta-skills infrastructure for Claude Code plugin ecosystem - skill authoring, hook development, modular design patterns, and evaluation frameworks
npx claudepluginhub athola/claude-night-market --plugin oracleDeploy ML models to production
Evaluate and compare ML model performance metrics
ML engineering plugin: Give your AI coding agent ML engineering superpowers.
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
When setting up local LLM inference without cloud APIs. When running GGUF models locally. When needing OpenAI-compatible API from a local model. When building offline/air-gapped AI tools. When troubleshooting local LLM server connections.
AI/ML development: LLM architecture, prompt engineering, ML ops, and NLP with production deployment focus