alexeldeib

This skill should be used when the user asks about "ripgrep", "rg command", "fast grep", "search files", "code search", "regex search in files", "find in files", "search codebase", "grep replacement", or needs guidance on file content searching, pattern matching, or recursive text search. Provides command reference, usage patterns, and best practices for ripgrep (rg).

This skill should be used when the user asks about "coding best practices", "code conventions", "code style", "how to write good code", "clean code", or asks for guidance on code quality and patterns. Scaffold skill - expand with your preferred practices.

This skill should be used when the user mentions "dots", "dot", "tasks", "task", "todo", "issue", "track", "plan", "breakdown", or asks about task management. Provides guidance for using the dots CLI task tracker.

This skill should be used when the user asks about "stacked branches", "git-spice", "gs command", "stacked PRs", "stacked pull requests", "stacked merge requests", "branch stacks", "restack branches", "submit stack", "gs branch", "gs stack", "gs upstack", "gs downstack", "gs repo sync", or needs help managing multiple dependent branches.

Use when coordinating AI agents as a military-style unit, applying this repo's AGENTS.md command hierarchy, fireteam/squad/platoon structure, relief protocol, D-Day-inspired command cadence, or mixed Codex/Claude task organization.

Use when the user explicitly asks for Agent Expeditionary Force doctrine, military-style agent coordination, fireteam/squad/platoon organization, D-Day-inspired command cadence, mixed Codex/Claude tasking, or relief of a stalled agent, assistant, tool, or plan.

Evaluates accuracy of quantized or unquantized LLMs using NeMo Evaluator Launcher (NEL). Triggers on "evaluate model", "benchmark accuracy", "run MMLU", "evaluate quantized model", "accuracy drop", "run nel". Handles deployment, config generation, and evaluation execution. Not for quantizing models (use ptq) or deploying/serving models (use deployment).

This skill should be used when the user asks to "quantize a model", "run PTQ", "post-training quantization", "NVFP4 quantization", "FP8 quantization", "INT8 quantization", "INT4 AWQ", "quantize LLM", "quantize MoE", "quantize VLM", or needs to produce a quantized HuggingFace or TensorRT-LLM checkpoint from a pretrained model using ModelOpt.