ralph-loop-yylo
ralph-loop-yylo is an code AI skill with a core value of Execute exactly one explicitly assigned YYLO Ledger task through the Ralph loop to a validated queued commit. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Execute exactly one explicitly assigned YYLO Ledger task through the Ralph loop to a validated queued commit. Use only when the user explicitly requests ralph-loop-yylo.
Quick Facts
mkdir -p ./skills/ralph-loop-yylo && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/ralph-loop-yylo/SKILL.md -o ./skills/ralph-loop-yylo/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Execute one assigned task in the Ralph loop
Read [references/implement.md](references/implement.md) completely and follow it.
Stay within the assigned task. Do not select unrelated work, edit `tasks.md`, auto-tag releases, push, deploy, mutate production, or broaden scope because another issue is noticed. Record a bounded related Kanban follow-up when necessary.
Keep durable instructions concise and evidence-backed. Status belongs in the task response and runtime receipts, not `AGENTS.md`.
Controller checkpoints are best-effort local durability warnings after terminal metadata is durable. They never gate `yy pi`, `yy task`, `yy merge`, product commits, candidates, or releases.
Complete assigned request
Treat the following as the complete user-assigned request. Preserve task references and directives literally; resolve them only through the normal agent workflow.
$ARGUMENTS
When to Use
- The user explicitly requests `ralph-loop-yylo` for one already-assigned YYLO Ledger task.
- You need to implement exactly that task through the validated loop to a queued, review-ready commit.
Limitations
- Exactly one assigned task per run: never select unrelated work, broaden scope, push, deploy, merge, release, or mutate production.
- Requires `yy task start TASK_ID` admission and `yy task finish TASK_ID` closure; stop after queueing - only the target owner runs `yy merge land`.
- Docs-only import: the upstream `scripts/kanban.sh` wrapper is intentionally not bundled; `references/` holds the worker contract.
- Controller checkpoints are best-effort durability warnings, never lifecycle gates.
Example
yy task start TASK_ID
yy task preflight TASK_ID
yy task finish TASK_ID> Adapted from [yylo-dev/yylo-skills](https://github.com/yylo-dev/yylo-skills) (MIT) - v2.0.1; frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: `scripts/kanban.sh` runtime not bundled.
🎯 Best For
- Claude users
- Software engineers
- Development teams
- Tech leads
💡 Use Cases
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply ralph-loop-yylo to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Is ralph-loop-yylo compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for ralph-loop-yylo?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install ralph-loop-yylo?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/ralph-loop-yylo/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.