Automate User Preferences lifecycle management across editing, versioning, QC, and reporting.
npx skills add https://github.com/jasonnamii/up-manager --skill up-manager
Please help me install this Agent Skill. Skill: up-manager Source: https://github.com/jasonnamii/up-manager/tree/main Command: npx skills add https://github.com/jasonnamii/up-manager --skill up-manager
UP-manager provides a unified workflow to manage all User Preferences (UP) settings across their lifecycle, including DSL editing, version bumps, path updates, QC validation, stability tracking, propagation, and reporting, reducing manual overhead and errors.
Trigger to add, modify, or manage preferences; the skill will run through the pipeline in a single turn.
High-intent search queries and answers about installing and using this skill.
You can automate version bumps and path updates for User Preferences settings by running the INIT→IG→EDIT→QC→TEAM_SYNC→REPORT pipeline, which automatically handles semantic versioning and path corrections while enforcing invariant guards to prevent regressions.
The best way to prevent personal custom changes from leaking into team preferences is to use a personal filter during team synchronization, ensuring that only approved modifications propagate to the shared configuration.
You can execute rapid L1 or L2 preference edits without running the full pipeline by triggering the one-turn fast path, which allows quick turnarounds while still maintaining strict file and code block handling.
Yes, you can use KR single-block DSL workflows for preference management, which are fully supported across the entire editing, versioning, and reporting lifecycle to ensure reproducible results.
QC validation works during the preference management pipeline by automatically checking stability and enforcing invariant guards after edits are applied, catching errors and preventing regressions before team synchronization and reporting occur.
You should use the full linear pipeline instead of fast-path edits when handling complex changes that require comprehensive stability tracking, team synchronization, and detailed reporting to ensure no regressions occur.
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