feedback
SolidManages OrchestKit learning system including feedback status, usage pattern tracking, and privacy/analytics consent. Supports pause/resume learning, data export, privacy policy display, and bug reporting. Tracks learned patterns and agent performance metrics. Use when reviewing learned patterns, pausing learning, or managing data consent.
Install
Quality Score: 86/100
Skill Content
Details
- Author
- yonatangross
- Repository
- yonatangross/orchestkit
- Created
- 5 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
spec-driven-feedback
Retrospective feedback system with Execute-Verify-Gate structural anti-skip enforcement for DevForgeAI operations. Captures feedback after /dev, /qa, /release, sprint planning, or manual triggers. Handles 5 feedback types: conversation, summary, metrics, checklist, and ai_analysis. Prevents token optimization bias through lean orchestration, per-phase reference loading, checkpoint persistence, and binary CLI gate enforcement. Use when feedback needs to be captured, when the user mentions retrospectives, lessons learned, workflow improvements, process feedback, or wants to review what went well or poorly. Also handles AI architectural analysis, feedback search, export/import, and configuration management.
feedback
Generate a retrospective report analyzing agent pipeline execution, duplication, scope adherence, and output quality from a completed work session.
interaction-feedback
Use when designing UI feedback around user actions and system state: loading, skeletons, optimistic updates, progress, success, errors, empty states, retries, disabled/pending states, autosave, undo, and perceived latency. Do NOT use for the words inside feedback (use `microcopy`), accessibility announcement mechanics (use `a11y`), business lifecycle modeling (use `state-machine-modeling`), or performance optimization (use `performance-engineering`).