ralph

name	ralph
keyword	ralph
description	Self-referential completion loop for AI CLI tools. Re-runs the agent on the same task across turns with fresh context each iteration, until the completion promise is detected or max iterations is reached.
allowed-tools	["Read","Write","Bash","Grep","Glob"]
tags	["ralph","ralph-loop","loop","completion","gemini-cli","opencode","self-referential"]
platforms	["Gemini-CLI","OpenCode","oh-my-opencode","Claude Code","Codex"]
version	2.0.0
source	gemini-cli-extensions/ralph

ralph - Self-Referential Completion Loop

When to use this skill

• Long-running implementation tasks that tend to stop early
• Tasks that need autonomous multi-turn iteration without manual intervention
• Workflows where the agent must self-correct and refine output across turns
• Sessions where exact completion signaling is required before stopping

---

Core Concept

The loop happens across agent turns, controlled by an AfterAgent hook.

1. You run ONCE: /ralph "Your task description" --completion-promise "DONE"
2. Agent works: Performs actions (modifies files, runs tests, writes code)
3. Hook intercepts: When the agent finishes its turn, the AfterAgent hook intercepts the exit
4. Loop continuation: Hook evaluates state (max iterations, promise) and starts a new turn with the original prompt, clearing the previous turn's context
5. Repeat: Continues autonomously until completion or user interruption

Why this works

• Stable Context & No Compaction: Prompt never changes between iterations; previous conversational context is cleared. The agent relies on current file state, not stale chat history.
• Persistent State: The agent's work persists in files and git history across iterations.
• Autonomous Improvement: Each iteration sees the current codebase state and improves on past work.
• Ghost Protection: If you interrupt the loop and start a new task, the hook detects the prompt mismatch and silently cleans up.

---

1. Core Command Pattern

/ralph "<task description>" [--completion-promise=TEXT] [--max-iterations=N]

Defaults:

• Completion promise: DONE
• Max iterations: 100

---

2. How the Loop Behaves

1. Starts with your task prompt.
2. On each turn end, the AfterAgent hook checks whether the assistant output contains:

<promise>DONE</promise>

3. If not found, hook starts a new agent turn with the same original prompt (context cleared).
4. Stops only when:
   • Completion promise is detected in output, or
   • Max iterations is reached, or
   • You run /ralph:cancel

---

3. Practical Usage

Standard run

/ralph "Build a Python CLI task manager with full test coverage"

With completion promise

/ralph "Build a REST API for todos. When all CRUD endpoints work and tests pass with >80% coverage, output TASK_COMPLETE" --completion-promise="TASK_COMPLETE"

Bounded iteration run

/ralph "Attempt to refactor the authentication module" --max-iterations=20

TDD workflow with self-correction

/ralph "Implement feature X by following TDD:
1. Write failing tests for the feature.
2. Implement the code to make the tests pass.
3. Run the test suite.
4. If any tests fail, analyze the errors and debug.
5. Refactor for clarity and efficiency.
6. Repeat until all tests are green.
7. When complete, output <promise>TESTS_PASSED</promise>" --completion-promise="TESTS_PASSED"

Cancel active loop

/ralph:cancel

View help

/ralph:help

---

4. Prompt Writing Best Practices

1. Clear Completion Criteria

Provide a verifiable definition of "done." The --completion-promise is crucial.

Good:

/ralph "Build a REST API for todos. When all CRUD endpoints are working and all tests pass with >80% coverage, you're complete." --completion-promise="TASK_COMPLETE"

2. Use Safety Hatches

Always use --max-iterations as a safety net to prevent infinite loops.

/ralph "Attempt to refactor the authentication module" --max-iterations=20

3. Encourage Self-Correction

Structure the prompt to guide the agent through work → verify → debug cycles.

---

5. Launch Safely

Always run in sandbox mode for safety. Enabling YOLO mode (-y) prevents constant tool execution prompts during the loop:

gemini -s -y

---

6. Installation (Gemini CLI)

gemini extensions install https://github.com/gemini-cli-extensions/ralph --auto-update

Required in ~/.gemini/settings.json:

{
  "hooksConfig": { "enabled": true },
  "context": {
    "includeDirectories": ["~/.gemini/extensions/ralph"]
  }
}

---

6. Codex에서 사용 (권장 보정)

ralph는 Gemini에서 AfterAgent 훅 기반으로 자동 반복되며, Codex는 현재 네이티브 종료-후크를 보장하지 않습니다.

따라서 Codex에서 ralph를 쓸 때는 아래 보정 스크립트를 설치해 사용하는 것을 권장합니다.

bash <your-agent-skills>/ralph/scripts/setup-codex-hook.sh

이 스크립트가 수행하는 것:

• ~/.codex/config.toml의 developer_instructions에 ralph 재시작 계약 정보를 기록
• ~/.codex/prompts/ralph.md 생성 (/prompts:ralph로 빠른 실행)
• --dry-run 옵션으로 적용 전 미리보기

Usage:
  bash <your-agent-skills>/ralph/scripts/setup-codex-hook.sh
bash <your-agent-skills>/ralph/scripts/setup-codex-hook.sh --dry-run

⚠️ 정확성 유의:

• Codex에서 완전 자동 루프를 강제하는 네이티브 훅은 현재 제한적입니다.
• 위 설정은 ralph 동작 계약을 고정시키고, 다음 작업을 반복할 때 수동 실수(/prompts:ralph 누락, promise 누락, max 반복 초과)를 줄여줍니다.

플랫폼별 적용 상태 (현재 지원 기준)

플랫폼	현재 지원 방식	핵심 조건
Gemini-CLI	네이티브	AfterAgent 훅 + ralph extension 설치
Claude Code	네이티브(권장)	스킬/오케스트레이션 적재 후 /ralph 사용
OpenCode	네이티브(동일 경로)	ralph 키워드 등록 후 동일 명령어 사용
Codex	보정 모드	setup-codex-hook.sh 실행 후 /prompts:ralph 기반 반복 운영

현재 스킬만으로 가능한지:

• Gemini-CLI/Claude Code/OpenCode: 가능
• Codex: setup-codex-hook.sh로 보정한 뒤 운영 가능

---

Quick Reference

Action	Command
Start loop	/ralph "task"
Custom promise	/ralph "task" --completion-promise=TEXT
Iteration cap	/ralph "task" --max-iterations=N
Cancel	/ralph:cancel
Help	/ralph:help