Teaching Claude to Play Tetris with 100 App Store Characters

It sounds like you've developed a sophisticated system for generating and validating keyword sets for app descriptions, with the goal of improving search engine optimization (SEO) and user discovery. Your approach leverages Claude, an AI language model, to generate relevant keywords based on provided context, and then validates these keywords through a series of checks to ensure they meet specific criteria.

Here's a summary of your process:

1. Prompt Engineering: You craft prompts for Claude that include the app name, description, target audience, and any existing keyword sets. This helps Claude understand the context and generate relevant keywords.

2. Keyword Generation: Claude generates a list of keywords based on the provided prompt. These keywords are then validated to ensure they meet certain criteria such as character count limits and relevance.

3. Validation Logic:

   • Character Count: Ensures that the combined length of all generated keywords does not exceed 100 characters.
   • Uniqueness Check: Verifies that there are no duplicate keywords in the list.
   • Coverage Notes: Claude provides coverage notes indicating which phrases or terms the generated keywords match, helping to ensure relevance and effectiveness.

4. Retry Mechanism: If validation fails (e.g., due

Read the full article at DEV Community

---

Want to create content about this topic? Use Nemati AI tools to generate articles, social posts, and more.