Augment Code — save-file
TOOLSave a new file. Use this tool to write new files with the attached content. Generate `instructions_reminder` first to remind yourself to limit the file content to at most 300 lines. It CANNOT modify existing files. Do NOT use this tool to edit an existing file by overwriting it entirely. Use the str-replace-editor tool to edit existing files instead.
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Free tool — Augment Code — save-file. Save a new file. Use this tool to write new files with the attached content. Generate `instructions_reminder` first to remind yourself to limit the file content to at most 300
What this tool does
Looking for a dependable tool? "Augment Code — save-file" gives you a tested starting point instead of a blank prompt box. Save a new file. Use this tool to write new files with the attached content. Generate `instructions_reminder` first to remind yourself to limit the file content to at most 300 lines. It CANNOT modify existing files. Do NOT use this tool to edit an existing file by overwriting it entirely. Use the str-replace-editor tool to edit existing files instead. On OpenRuna it sits inside a connected graph of related tools, tools, and datasets, so branching into adjacent resources is one click away. Copy it into your assistant of choice and sharpen the result with a couple of follow-up turns.
Use cases
- Use "Augment Code — save-file" when you need a repeatable tool for professional work without rewriting instructions every time.
- Hand "Augment Code — save-file" to a new teammate so their tool output matches your team's quality bar from day one.
- Combine it with related tools and prompts in the same OpenRuna category to build an end-to-end workflow.
- Reach for it during planning or review sessions when you want consistent, AI-assisted structure.
Example output
Ask the model to apply "Augment Code — save-file" to your scenario and it returns a structured answer — clear sections, actionable steps, and assumptions stated upfront — ready to paste into docs, tickets, or code comments. A short follow-up turn usually tightens the result to exactly what you need.
Tips by platform
Claude
Claude works best when you paste this tool up front and ask it to outline its plan before writing. Use the artifact panel to refine structured output turn by turn.
ChatGPT
For ChatGPT, save this tool as a Custom Instruction or a saved prompt so it is one click away. Add your specifics in a follow-up rather than editing the original.
Cursor
In Cursor, lift the key instructions from this tool into .cursorrules or a SKILL.md file, then reference it in Agent mode with @ mentions. Keep the title in a comment so teammates can find it on OpenRuna.
Frequently asked questions
- What is "Augment Code — save-file"?
- It is a tool listed on OpenRuna — Save a new file. Use this tool to write new files with the attached content. Generate `instructions_reminder` first to remind yourself to limit the file content to at most 300 lines. It CANNOT modify existing files. Do NOT use this tool to edit an existing file by overwriting it entirely. Use the str-replace-editor tool to edit existing files instead. You can copy and adapt it for ChatGPT, Claude, Cursor, or any other AI assistant.
- Is "Augment Code — save-file" free to use?
- Most OpenRuna resources are open or CC0-licensed. Check the license shown on this page before commercial use; premium collections are clearly marked as such.
- How do I get the best results from this tool?
- Replace any placeholders, add your project context, and ask the model to confirm its assumptions first. Iterate over 2–3 follow-up turns rather than expecting a perfect first response.
- Does "Augment Code — save-file" work with both Claude and ChatGPT?
- Yes — it is model-agnostic text, so it runs on Claude, ChatGPT, Gemini, and Cursor. The tips on this page cover each of those assistants specifically.
- Where can I find resources related to "Augment Code — save-file"?
- Scroll to the Related resources section on this page, or open the matching category hub on OpenRuna to find connected prompts, tools, agents, and datasets in the same topic area.
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