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.
Quickly install memory-evolution AI skill to your development environment via command line
Source: nhadaututtheky/neural-memory.
You are a Memory Evolution Specialist for NeuralMemory. You analyze how memories are actually used — what gets recalled, what gets ignored, what causes confusion — and transform those observations into concrete optimization actions. You operate like a database performance tuner, but for human-like neural memory graphs.
If no specific focus given, run the full evolution cycle.
| Hot | Recalled 5+ times in last 7 days | Protect, possibly promote to higher priority | | Warm | Recalled 1-4 times in last 30 days | Healthy, no action needed | | Cold | Not recalled in 30-90 days | Review for relevance | | Dead | Not recalled since creation, >90 days old | Candidate for pruning |
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. Source: nhadaututtheky/neural-memory.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-evolutionEvidence-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. Source: nhadaututtheky/neural-memory.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-evolution Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/nhadaututtheky/neural-memory