💻 Coding & Development

Note Guru

📁 Coding & Development 👤 Contributed by @sigma.sauer07@gmail.com 🗓️ Updated
The prompt
Analyze all files in the folder named '${main_folder}` located at `${path_to_folder}`/ and perform the following tasks: ## Task 1: Extract Sensitive Data Review every file thoroughly and identify all sensitive information including API keys, passwords, tokens, credentials, private keys, secrets, connection strings, and any other confidential data. Create a new file called `secrets.md` containing all discovered sensitive information with clear references to their source files. ## Task 2: Organize by Topic After completing the secrets extraction, analyze the content of each file again. Many files contain multiple unrelated notes written at different times. Your job is to: 1. Identify the '${topic_max}' most prominent topics across all files based on content frequency and importance 2. Create '${topic_max}' new markdown files, one for each topic, named `${topic:#}.md` where you choose descriptive topic names 3. For each note segment in the original files: - Copy it to the appropriate topic file - Add a reference number in the original file next to that note (e.g., `${topic:2}` or `→ Security:2`) - This reference helps verify the migration later ## Task 3: Archive Original Files Once all notes from an original file have been copied to their respective topic files and reference numbers added, move that original file into a new folder called `${archive_folder:old}`. ## Expected Final Structure ``` ${main_folder}/ ├── secrets.md (1 file) ├── ${topic:1}.md (topic files total) ├── ${topic:2}.md ├── ..... (more topic files) ├── ${topic:#}.md └── ${archive_folder:old}/ └── (all original files) ``` ## Important Guidelines - Be thorough in your analysis—read every file completely - Maintain the original content when copying to topic files - Choose topic names that accurately reflect the content clusters you find - Ensure every note segment gets categorized - Keep reference numbers clear and consistent - Only move files to the archive folder after confirming all content has been properly migrated Begin with `${path_to_folder}` and let me know when you need clarification on any ambiguous content during the organization process.

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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