Analyze a complete literary work into a structured Basic Memory knowledge graph. Covers schema design, entity seeding, chapter-by-chapter processing, cross-referencing, validation, and visualization.

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 Phase 0: Setup Create the Project Use a kebab case slug of the work's title (e.g., great gatsby , hamlet , beloved ). Define Schemas Write 6 schema notes to schema/ . Each schema defines the entity type's fields, observation categories, and relation types. Adapt fields to fit the work — the schemas below are starting points, not rigid templates. Character Schema Add work specific fields as needed — e.g., rank for military fiction, house for family sagas, species for fantasy. Theme Schema Chapter Schema Location Schema Symbol Schema LiteraryDevice Schema Directory Structure Phase 1: Seed Entities Before processing chapters, create stub notes for major entities so [[wiki links]] resolve from the start. Characters (major) For each major character, create a stub with known metadata: Seed Checklist Identify the work's major entities before you start reading. A good starting inventory: Type Typical Count What to Include Characters (major) 8 20 Protagonist, antagonist, key supporting cast Themes 5 12 Central concerns the work explores Locations 4 10 Primary settings, symbolically significant places Symbols 4 10 Recurring objects, images, or motifs with layered meaning Stubs don't need to be complete — they give [[wiki link]] targets and will be enriched during chapter processing. Phase 2: Chapter Processing Source Text Preparation Obtain the full text and identify chapter/section boundaries. For public domain works, Project Gutenberg is a good source. For copyrighted works, work from a physical or licensed digital copy. Batching Strategy Process ~10 chapters per batch to balance depth with progress. Group by narrative arc or thematic focus: Batch Typical Content 1 Opening: setting, character introductions, world building 2 3 Rising action: conflicts established, relationships develop 4 6 Middle: complications, turning points, thematic deepening 7 8 Climax approach: escalation, revelations, crises Final Climax, resolution, epilogue Adjust batch size based on chapter length and density. Short, action heavy chapters can be batched in larger groups; long, philosophically dense chapters may need smaller batches. Per Chapter Workflow For each chapter: 1. Read the chapter carefully. If working from a source text file, read the relevant section. 2. Create the chapter note: 3. Enrich related entities: 4. Track progress using the memory tasks skill to create a processing task that survives context compaction. What to Capture Per Chapter Category What to Look For [summary] 1 2 sentence chapter synopsis [event] Key plot events (actions, revelations, arrivals) [tone] Emotional and stylistic atmosphere [technique] Narrative innovations (POV shifts, structural experiments, genre blending) [quote] Memorable or thematically significant passages [significance] Why this chapter matters to the whole [foreshadowing] Hints at future events Entity Enrichment Per Chapter As each chapter is processed, append observations to relevant entities: Characters : [arc] moments, new [trait] revelations, [quote] attributions Themes : [manifestation] in this chapter, [evolution] shifts Symbols : [appearance] with context, new [interpretation] angles Locations : [atmosphere] as described, [significance] in scene Literary devices : [example] from this chapter Adding Prose and Interpretation After the structured observations are in place, consider adding interpretive prose to major entity notes. Prepend 2 4 paragraphs of critical essay before the Observations section using edit note(operation="prepend") . This prose should: Argue for a reading of the character, theme, or symbol — not just describe it Connect the entity to the work's larger concerns and to literary tradition Include subjective opinions clearly marked as such ("In my reading...", "I find...") Ground claims in textual evidence cited by chapter number The prose adds the interpretive texture that structured observations alone cannot capture. Phase 3: Cross Referencing After all chapters are processed: Character Arcs For each major character, write a full [arc] summary observation covering their trajectory across the work. Theme Evolution For each theme, add [evolution] observations tracing how it develops from introduction to resolution. Chapter Parallels Add parallels and contrasts with relations between structurally similar chapters (e.g., mirrored scenes, repeated settings, thematic echoes). Analysis Notes Create synthesis notes in analysis/ : Recommended analysis notes: Narrative Structure — overall architecture and pacing Work Overview — synthesis of the complete work (summary, thesis, legacy) Critical Reception — historical and contemporary interpretations Discover Emergent Entities During chapter processing, new minor characters, locations, and symbols will emerge. Create notes for any that appear in 3+ chapters or carry thematic weight. Phase 4: Validation Schema Validation Drift Detection Fix issues found — common fixes: Missing required observation categories → add them via edit note Enum values outside allowed set → correct metadata Fields in notes but not schema → add as optional to schema if legitimate Relation Consistency Spot check bidirectional relations: if Chapter X features [[Character]] , does Character have observations referencing Chapter X? Fix gaps. Phase 5: Visualization Generate canvas files for visual exploration: Adapting to Other Genres This pipeline works for any literary text. Adjust schemas for genre: Genre Schema Adjustments Novel Base schemas work as is; add genre specific Character fields as needed Play Add Act and Scene schemas; Character gets speaking lines field Poetry collection Replace Chapter with Poem ; add form , meter , rhyme scheme fields Non fiction Replace Chapter with Section ; add Argument , Evidence schemas Short story collection Add Story schema with narrator , setting , word count Epic/myth Add Deity , Prophecy schemas; Location gets mythological significance Memoir Character schema gets relationship to narrator ; add Memory schema Scaling Guidance Work Length Batch Size Estimated Notes Novella (~40K words) 5 10 chapters ~50 80 Novel (~80K words) 8 12 chapters ~100 150 Long novel (~200K+ words) 10 15 chapters ~200 300 Series (multiple volumes) 1 volume at a time ~200+ per volume Related Skills memory schema — Schema creation, validation, and drift detection memory tasks — Track chapter processing progress across context compaction memory notes — Note writing patterns, observation categories, wiki links memory ingest — Processing external input into structured entities memory metadata search — Querying notes by frontmatter fields memory lifecycle — Archiving completed analysis phases Guidelines Seed before processing. Create entity stubs first so wiki links resolve immediately during chapter processing. Batch for sanity. Processing ~10 chapters at a time balances depth with momentum. Track progress with a Task note. Read the source text. Don't rely on memory or summaries. Read (or re read) the actual text for each batch before creating notes. Textual evidence is everything. Observations are your index. The knowledge graph's value comes from categorized observations. Be generous with categories and specific with content. Relations are your web. Every chapter should link to characters, themes, locations, and devices. Every entity should link back to chapters where it appears. Enrich iteratively. Entity notes grow richer with each chapter. Don't try to write the perfect character note upfront — append as you go. Add prose for depth. After structured data is in place, add interpretive essays to major notes. The prose captures what observations cannot: argument, nuance, opinion, and voice. Validate periodically. Run schema validate after each batch, not just at the end. Catch drift early. Quote generously. Literary analysis lives on textual evidence. Include significant quotes as [quote] observations with chapter attribution. Review and revise. After completing all chapters, review the full graph from an external perspective. Look for thin notes, missing connections, and gaps in coverage. The first pass is never the last. Analysis comes last. Synthesis notes in analysis/ should be written after all chapters are processed, when you have the full picture.

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