skill-updater

To update an AI skill based on user feedback, you need a process that analyzes the feedback and modifies the skill's files. This Skill systematically integrates bug reports or missing features by updating the core documentation, scripts, and reference files.

Iterative AI skill improvement is the process of refining skill performance over time. It involves analyzing existing skill structures, integrating user-reported issues, and applying modifications to the skill files to ensure continued accuracy and effectiveness.

To fix a skill that doesn't trigger correctly, you must update its discoverability metadata. This involves analyzing the skill's description and modifying the documentation frontmatter to better match expected search queries and user intents.

Yes, you can modify both skill scripts and documentation. The update process requires analyzing the entire skill structure, including the main documentation, the scripts directory, and the references directory, to implement and validate necessary changes.

The best way to integrate missing features is through a guided update process. This involves systematically addressing the user feedback, applying the necessary modifications to the skill's code and documentation, and validating the final performance.