Agent skill

yeet

Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).

Stars 23,776
Forks 2,298

Install this agent skill to your Project

npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/workflow-automation/yeet

SKILL.md

Prerequisites

  • Require GitHub CLI gh. Check gh --version. If missing, ask the user to install gh and stop.
  • Require authenticated gh session. Run gh auth status. If not authenticated, ask the user to run gh auth login (and re-run gh auth status) before continuing.

Naming conventions

  • Branch: codex/{description} when starting from main/master/default.
  • Commit: {description} (terse).
  • PR title: [codex] {description} summarizing the full diff.

Workflow

  • If on main/master/default, create a branch: git checkout -b "codex/{description}"
  • Otherwise stay on the current branch.
  • Confirm status, then stage everything: git status -sb then git add -A.
  • Commit tersely with the description: git commit -m "{description}"
  • Run checks if not already. If checks fail due to missing deps/tools, install dependencies and rerun once.
  • Push with tracking: git push -u origin $(git branch --show-current)
  • If git push fails due to workflow auth errors, pull from master and retry the push.
  • Open a PR and edit title/body to reflect the description and the deltas: GH_PROMPT_DISABLED=1 GIT_TERMINAL_PROMPT=0 gh pr create --draft --fill --head $(git branch --show-current)
  • Write the PR description to a temp file with real newlines (e.g. pr-body.md ... EOF) and run pr-body.md to avoid \n-escaped markdown.
  • PR description (markdown) must be detailed prose covering the issue, the cause and effect on users, the root cause, the fix, and any tests or checks used to validate.

Expand your agent's capabilities with these related and highly-rated skills.

davila7/claude-code-templates

verl-rl-training

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

23,776 2,298
Explore
davila7/claude-code-templates

openrlhf-training

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.

23,776 2,298
Explore
davila7/claude-code-templates

gguf-quantization

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

23,776 2,298
Explore
davila7/claude-code-templates

Claude Code Guide

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

23,776 2,298
Explore
davila7/claude-code-templates

qdrant-vector-search

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

23,776 2,298
Explore
davila7/claude-code-templates

behavioral-modes

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

23,776 2,298
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results