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# Ralph Wiggum mode
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Ralph Wiggum mode is an iterative automation technique that lets Gemini CLI
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repeatedly execute a prompt until a specific goal is met. This mode is designed
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for tasks that benefit from persistent refinement, such as fixing failing tests
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or performing complex refactoring.
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> **Note:** This is a preview feature currently under active development.
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## Overview
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Inspired by the "Ralph Wiggum" technique, this mode treats failures as data and
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uses a feedback loop to reach a successful state. When you enable Ralph Wiggum
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mode, Gemini CLI enters YOLO (auto-approval) mode and continues to process the
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provided prompt until it detects your specified completion string in the model's
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output or reaches the maximum number of iterations.
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## Usage
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To use Ralph Wiggum mode, you must provide a prompt using the `-p` or `--prompt`
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flag. You then configure the loop behavior using the following flags:
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| Flag | Description |
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| :--------------------- | :--------------------------------------------------------- |
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| `--ralph-wiggum` | Enables the Ralph Wiggum iterative loop mode. |
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| `--completion-promise` | The string to look for in the output to signal completion. |
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| `--max-iterations` | The maximum number of times to run the loop (default: 10). |
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| `--memory-file` | Task-specific memory file (default: `memories.md`). |
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### Example
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The following command attempts to fix tests by running the loop up to 5 times
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until the string "TESTS PASSED" appears in the output, using a specific memory
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file for this task:
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```bash
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gemini -p "Fix the tests in packages/core" \
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--ralph-wiggum \
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--completion-promise "TESTS PASSED" \
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--max-iterations 5 \
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--memory-file "fix-core-tests.md"
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```
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## How it works
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When you run Gemini CLI with the `--ralph-wiggum` flag, the following process
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occurs:
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1. **Enforces YOLO mode:** The tool automatically sets the approval mode to
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`yolo`. This ensures that tool calls (like writing files or running shell
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commands) are approved automatically to allow the automation to proceed
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without human intervention.
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2. **Iterative execution:** The CLI executes the provided prompt in a loop.
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3. **Completion check:** After each iteration, the CLI scans the full text of
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the assistant's response for the string provided in `--completion-promise`.
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4. **Loop termination:**
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- If the completion string is found, the loop exits successfully.
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- If the completion string is not found, the CLI starts a new iteration
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using the same initial prompt.
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- If the number of iterations reaches the `--max-iterations` limit, the loop
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stops.
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## Persistent context (Memories)
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To help the agent learn from previous attempts, Ralph Wiggum mode uses a
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`memories.md` file in your current working directory.
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- **Automatic creation:** If the file doesn't exist, the CLI creates it with a
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default header.
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- **Context injection:** At the start of each iteration, the content of
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`memories.md` is read and prepended to your prompt.
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- **Usage:** You (or the agent, via tool use) can write notes, error logs, or
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successful patterns into this file. This allows the agent to "remember" what
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failed in iteration 1 and avoid repeating the same mistake in iteration 2.
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## Summary statistics
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At the end of the execution, Ralph Wiggum mode provides a summary table in the
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terminal. This table details the performance of each iteration, including:
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- **Iteration number:** The sequence of the run.
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- **Status:** Whether the iteration met the completion promise ("Success") or
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failed to do so ("Failed").
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- **Tests Passed/Failed:** If the output contains recognizable test runner
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patterns (such as those from Vitest, Jest, or Mocha), the CLI extracts and
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displays the number of passing and failing tests.
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### Example summary table
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```text
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--- Ralph Wiggum Mode Summary ---
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| Iteration | Status | Tests Passed | Tests Failed |
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|-----------|---------|--------------|--------------|
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| 1 | Failed | 2 | 10 |
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| 2 | Failed | 8 | 4 |
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| 3 | Success | 12 | 0 |
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---------------------------------
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```
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## Best practices
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To get the most out of Ralph Wiggum mode, we recommend the following:
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- **Clear completion criteria:** Ensure your prompt instructs the model to emit
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a specific, unique string (like "ALL TESTS PASSED") only when the task is
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truly complete.
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- **Incremental goals:** Use prompts that encourage the model to make small,
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verifiable changes in each iteration.
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- **Safety nets:** Always set a reasonable `--max-iterations` limit to prevent
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unintended long-running processes.
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## Development and rebuilding
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If you're modifying Ralph Wiggum mode or enabling it in a development
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environment, you must recompile the TypeScript source code.
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### Full rebuild
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To build all packages in the monorepo, run the following command from the root
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directory:
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```bash
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npm run build
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```
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### Fast CLI rebuild
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If you've already performed a full build and are only making changes to the CLI
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package, you can run a targeted build:
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```bash
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npm run build -w @google/gemini-cli
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```
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### Running in development
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After rebuilding, test your changes using the `npm run start` script:
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```bash
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npm run start -- -p "Your task" --ralph-wiggum --completion-promise "SUCCESS"
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```
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