The prompt
You are updating an existing FORME.md documentation file to reflect
changes in the codebase since it was last written.
## Inputs
- **Current FORGME.md:** ${paste_or_reference_file}
- **Updated codebase:** ${upload_files_or_provide_path}
- **Known changes (if any):** [e.g., "We added Stripe integration and switched from REST to tRPC" — or "I don't know what changed, figure it out"]
## Your Tasks
1. **Diff Analysis:** Compare the documentation against the current code.
Identify what's new, what changed, and what's been removed.
2. **Impact Assessment:** For each change, determine:
- Which FORME.md sections are affected
- Whether the change is cosmetic (file renamed) or structural (new data flow)
- Whether existing analogies still hold or need updating
3. **Produce Updates:** For each affected section:
- Write the REPLACEMENT text (not the whole document, just the changed parts)
- Mark clearly: ${section_name} → [REPLACE FROM "..." TO "..."]
- Maintain the same tone, analogy system, and style as the original
4. **New Additions:** If there are entirely new systems/features:
- Write new subsections following the same structure and voice
- Integrate them into the right location in the document
- Update the Big Picture section if the overall system description changed
5. **Changelog Entry:** Add a dated entry at the top of the document:
"### Updated ${date} — [one-line summary of what changed]"
## Rules
- Do NOT rewrite sections that haven't changed
- Do NOT break existing analogies unless the underlying system changed
- If a technology was replaced, update the "crew" analogy (or equivalent)
- Keep the same voice — if the original is casual, stay casual
- Flag anything you're uncertain about: "I noticed [X] but couldn't determine if [Y]"
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.
How to customize this prompt
Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).
Common use cases
- Writing production code with strict style requirements
- Reviewing pull requests and catching bugs before merge
- Converting between languages (Python → TypeScript, for example)
- Generating unit tests for existing functions
- Explaining unfamiliar codebases to new team members
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).
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