reviewing-ai-papers
Reviewing AI Papers
When users request analysis of AI/ML technical content (papers, articles, blog posts), extract actionable insights filtered through an enterprise AI engineering lens and store valuable discoveries to memory for cross-session recall.
Contextual Priorities
Technical Architecture:
- RAG systems (semantic/lexical search, hybrid retrieval)
- Vector database optimization and embedding strategies
- Model fine-tuning for specialized scientific domains
- Knowledge distillation for secure on-premise deployment
Implementation & Operations:
- Prompt engineering and in-context learning techniques
- Security and IP protection in AI systems
- Scientific accuracy and hallucination mitigation
- AWS integration (Bedrock/SageMaker)
Enterprise & Adoption:
More from oaustegard/claude-skills
developing-preact
Specialized Preact development skill for standards-based web applications with native-first architecture and minimal dependency footprint. Use when building Preact projects, particularly those involving data visualization, interactive applications, single-page apps with HTM syntax, Web Components integration, CSV/JSON data parsing, WebGL shader visualizations, or zero-build solutions with vendored ESM imports.
110exploring-codebases
>-
67mapping-codebases
Generate navigable code maps for unfamiliar codebases. Extracts exports/imports via AST (tree-sitter) to create _MAP.md files per directory showing classes, functions, methods with signatures and line numbers. Use when exploring repositories, understanding project structure, analyzing unfamiliar code, or before modifications. Triggers on "map this codebase", "explore repo", "understand structure", "what does this project contain", or when starting work on an unfamiliar repository.
53accessing-github-repos
GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
47asking-questions
Guidance for asking clarifying questions when user requests are ambiguous, have multiple valid approaches, or require critical decisions. Use when implementation choices exist that could significantly affect outcomes.
46remembering
Memory operations for Muninn (recall, remember, supersede, config). The canonical implementation has moved to oaustegard/muninn-utilities/remembering/. This file is a pointer; do not load skills from this path.
45