memory-literary-analysis
Memory Literary Analysis
Transform a complete literary work into a structured knowledge graph. Characters, themes, chapters, locations, symbols, and literary devices become interconnected notes — searchable, validatable, and visualizable.
When to Use
- Analyzing a novel, play, poem, or non-fiction book end-to-end
- Building a teaching or study resource for a literary text
- Creating a book club companion knowledge base
- Research projects requiring structured close reading
- Stress-testing Basic Memory at scale (~200+ notes, 1000+ relations)
Pipeline Overview
More from basicmachines-co/basic-memory-skills
memory-notes
How to write well-structured Basic Memory notes: frontmatter, observations with semantic categories, relations with wiki-links, and best practices for building a rich knowledge graph. Use when creating or improving notes.
433memory-reflect
Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cron, heartbeat, or explicit request to reflect on recent activity. Runs as background processing to improve memory quality over time.
404memory-tasks
Task management via Basic Memory schemas: create, track, and resume structured tasks that survive context compaction. Uses BM's schema system for uniform notes queryable through the knowledge graph.
301memory-defrag
Defragment and reorganize agent memory files: split bloated files, merge duplicates, remove stale information, and restructure the memory hierarchy. Use when memory files have grown unwieldy, contain redundancies, or need reorganization. Run periodically (weekly) or on demand.
291memory-metadata-search
Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Use when finding notes by status, priority, confidence, or any custom YAML field rather than free-text content.
282memory-schema
Schema lifecycle management for Basic Memory: discover unschemaed notes, infer schemas, create and edit schema definitions, validate notes, and detect drift. Use when working with structured note types (Task, Person, Meeting, etc.) to maintain consistency across the knowledge graph.
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