What problem does it solve?
Manually updating changelogs is a repetitive, error-prone task that often leads to inconsistent formatting and excessive token usage in AI contexts. This Skill automates the process, ensuring your CHANGELOG.md and TEST-CHANGELOG.md are always perfectly formatted, concise, and optimized for AI processing, saving you significant time and effort.
Core Features & Use Cases
- Automated Entry Creation: Automatically generates and inserts new changelog entries into the correct sections (
Added, Changed, Fixed).
- Token Optimization: Applies advanced techniques like using tables over prose and consolidating redundancy to drastically reduce the token count of changelog entries, making AI interactions more efficient.
- Format Enforcement: Guarantees adherence to "Keep a Changelog" standards, including date formats, title patterns, and metric inclusion, ensuring consistency across your project.
- Use Case: After completing a new feature or a critical bug fix, simply instruct the AI to "update the changelog." The Skill will then craft a concise, token-optimized, and perfectly formatted entry, reflecting the changes and their impact, without any manual intervention from you.
Quick Start
Update the CHANGELOG.md with a new entry for the recently implemented user authentication feature.
The feature involved adding JWT support and updating the login flow.
It resulted in a 15% reduction in login time.