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Found 5 Skills
Proactively summarize and consolidate knowledge from AI conversation sessions. Auto-triggers when: (1) Starting a new session after meaningful previous work, (2) Session contains significant learnings worth preserving. Captures debugging insights, architecture decisions, patterns, configs, and lessons learned into structured knowledge documents. Explicit triggers: 'summarize', 'consolidate', 'save knowledge', 'document this'.
Merges mature lessons from a domain memory file into its instruction file. Syntax: `/memory-merger >domain [scope]` where scope is `global` (default), `user`, `workspace`, or `ws`.
Evidence-based memory optimization from real usage patterns. Analyzes recall performance, identifies bottlenecks, suggests consolidation/pruning/enrichment, and tracks improvement over time via checkpoint Q&A.
Neural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.
Use when beo learnings need a manual consolidation pass across multiple completed features, especially when learnings have gone stale, repeated patterns are accumulating, or the user asks to consolidate, clean up, merge, or promote existing learnings. This is the periodic learnings-sweep skill, not the per-feature compounding step. Use for prompts like "run dream", "consolidate learnings", "merge repeated learnings", or "do a learnings pass".