Post Mortem

Use this when reviewing AEM Edge Delivery Services (EDS, Franklin, Helix) code, either self-review at the end of development before opening a PR, or reviewing an existing pull request. Validates block structure, CSS and JS patterns, DOM output, Lighthouse performance, and accessibility against EDS best practices, and posts findings as review comments or GitHub suggestions.

Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.

Provide qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.

Comprehensive Nushell scripting best practices, idioms, security, and code review. Use when writing, reviewing, auditing, debugging, or refactoring Nushell (.nu) scripts, modules, custom commands, pipelines, and tests. Also use for Bash/POSIX-to-Nushell conversion and Nu 0.114+ migration issues such as stricter type checking, `run`, SemVer, optional `nothing`, subprocess diagnostics, and explicit submodule imports.

Generate AI images using Gemini or GPT APIs directly. Covers model selection (Gemini for scenes; GPT Image 2 for text rendering, batch variations, multi-reference compositing; GPT Image 1.5 for transparent icons), the 5-part prompting framework, API calling patterns, multi-turn editing, and quality assurance. Produces photorealistic scenes, icons, illustrations, OG images, posters, infographics, and product shots. Use when building websites that need images, creating marketing assets, or generating visual content. Triggers: 'generate image', 'ai image', 'create hero image', 'make an icon', 'generate illustration', 'create og image', 'poster', 'infographic', 'image variations', 'gpt-image-2', 'ai art', 'image generation'.

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.