Dataojitori/nocturne_memory

Belief Duel resolves contradictions in an AI's memory graph when two accepted beliefs cannot logically coexist. Use it when sibling memories conflict or a child node challenges a parent node's default belief.

Memory Audit is an entry point for auditing an AI agent's memory. It routes symptoms like stale or bloated memories to sub-skills for pruning, extracting patterns, and resolving contradictions.

Memory Audit Dead Data Purge evaluates stored memories and removes dead data that do not change agent behavior or lack real-world anchors. Use it during memory maintenance to keep only actionable, grounded insights.

Memory Audit Node Decomposition breaks an overstuffed memory node into focused independent nodes when a single disclosure cannot cover all its concepts. Use it when a memory exceeds 800 tokens, mixes unrelated concepts, or triggers jump-reading.

Memory Audit Pattern Extraction reviews an agent's memory network for repeated failures, identifies why prior 'antidote' memories did not prevent recurrence, and rewrites them with stronger triggers and positive mindset anchors. Use it when several memories describe the same lesson or the same mistake recurs.

Memory Discoverability Audit reviews an AI agent's stored memories to verify parent placement, disclosure triggers, aliases, and priority so each memory surfaces at the right moment. Use it when a memory fails to surface, trigger conditions are vague, or a parent has more than ten children.