LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine…
Codex-compatible Ralph loop runner with dual engines (compat local state loop + optional open-ralph-wiggum backend).
Claude Code
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop --agent claude-code
Codex
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a codex -y
Cursor
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a cursor -y
Gemini CLI
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a gemini-cli -y
GitHub Copilot
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a github-copilot -y
OpenCode
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a opencode -y
Windsurf
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill ralph-loop -a windsurf -y
name: ralph-loop description: Codex-compatible Ralph loop runner with dual engines (compat local state loop + optional open-ralph-wiggum backend).
This is a Codex-oriented `ralph-loop` command with two execution engines.
$codexHome = if ($env:CODEX_HOME) { $env:CODEX_HOME } else { Join-Path $HOME '.codex' }
$script = Join-Path $codexHome 'skills/ralph-loop/scripts/ralph-loop.ps1'
# Start a local compat loop
powershell -ExecutionPolicy Bypass -File $script Build a todo API --max-iterations 20 --completion-promise DONE
# Move to the next iteration manually
powershell -ExecutionPolicy Bypass -File $script --next
# Show current loop state
powershell -ExecutionPolicy Bypass -File $script --status
# Force restart with a new prompt
powershell -ExecutionPolicy Bypass -File $script New prompt --max-iterations 10 --force
# Use open-ralph-wiggum backend (auto loop, defaults to --agent codex and --no-commit)
powershell -ExecutionPolicy Bypass -File $script --engine open Build a todo API --max-iterations 20 --completion-promise DONEIntelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
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