memory-literary-analysis by basicmachines-co/basic-memory-skills
npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-literary-analysis将完整的文学作品转化为结构化的知识图谱。人物、主题、章节、地点、象征和文学手法成为相互关联的笔记——可搜索、可验证、可可视化。
Phase 0: Setup → 项目、模式、目录结构
Phase 1: Seed → 已知主要实体的存根笔记
Phase 2: Process → 分批处理逐章笔记
Phase 3: Cross-ref → 丰富弧线,添加平行关系,撰写分析
Phase 4: Validate → 模式检查、漂移检测、一致性检查
Phase 5: Visualize → 用于人物关系网、时间线的画布文件
create_memory_project(name="<work-name>", path="~/basic-memory/<work-name>")
使用作品标题的 kebab-case 形式(例如 great-gatsby、hamlet、beloved)。
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在 schema/ 目录下编写 6 个模式笔记。每个模式定义实体类型的字段、观察类别和关系类型。根据作品调整字段——下面的模式是起点,不是严格的模板。
write_note(
title="Character",
directory="schema",
note_type="schema",
metadata={
"entity": "Character",
"version": 1,
"schema": {
"role(enum)": "[protagonist, antagonist, supporting, minor], character's narrative role",
"description": "string, brief character description",
"first_appearance?": "string, chapter or scene of first appearance",
"status?(enum)": "[alive, dead, unknown, transformed], character status at end of work"
},
"settings": {"validation": "warn"}
},
content="""# Character
Schema for character entity notes.
## Observations
- [convention] Major characters in characters/major/, minor in characters/minor/
- [convention] Observation categories: trait, motivation, arc, quote, appearance, relationship, symbolism, fate
- [convention] Relations: appears_in, contrasts_with, allied_with, commands, symbolizes, associated_with"""
)
根据需要添加作品特定的字段——例如,军事小说用 rank,家族传奇用 house,奇幻作品用 species。
write_note(
title="Theme",
directory="schema",
note_type="schema",
metadata={
"entity": "Theme",
"version": 1,
"schema": {
"description": "string, what this theme explores",
"prevalence(enum)": "[major, minor], how central to the work",
"first_introduced?": "string, where theme first appears"
},
"settings": {"validation": "warn"}
},
content="""# Theme
Schema for thematic analysis notes.
## Observations
- [convention] Observation categories: definition, manifestation, evolution, counterpoint, quote, interpretation
- [convention] Relations: embodied_by, contrasts_with, reinforced_by, explored_in, expressed_through"""
)
write_note(
title="Chapter",
directory="schema",
note_type="schema",
metadata={
"entity": "Chapter",
"version": 1,
"schema": {
"chapter_number": "integer, sequential chapter number",
"pov?": "string, point-of-view character or narrator mode",
"setting?": "string, primary location",
"narrative_mode?(enum)": "[dramatic, expository, reflective, epistolary, mixed], chapter's primary mode"
},
"settings": {"validation": "warn"}
},
content="""# Chapter
Schema for chapter-level analysis notes.
## Observations
- [convention] Chapters stored in chapters/ directory
- [convention] Observation categories: summary, event, tone, technique, quote, significance, foreshadowing
- [convention] Relations: features, set_in, explores, contains, employs, follows, precedes, parallels"""
)
write_note(
title="Location",
directory="schema",
note_type="schema",
metadata={
"entity": "Location",
"version": 1,
"schema": {
"description": "string, what this place is",
"location_type(enum)": "[city, building, landscape, body_of_water, region, fictional, vehicle], type of place",
"real_or_fictional(enum)": "[real, fictional, both], whether the place exists"
},
"settings": {"validation": "warn"}
},
content="""# Location
Schema for location and setting notes.
## Observations
- [convention] Observation categories: description, atmosphere, symbolism, significance, geography
- [convention] Relations: setting_for, associated_with, symbolizes, contains, part_of"""
)
write_note(
title="Symbol",
directory="schema",
note_type="schema",
metadata={
"entity": "Symbol",
"version": 1,
"schema": {
"description": "string, what the symbol is literally",
"symbol_type(enum)": "[object, animal, color, action, natural_phenomenon, body_part], category of symbol",
"primary_meaning": "string, most common interpretation"
},
"settings": {"validation": "warn"}
},
content="""# Symbol
Schema for symbolic element notes.
## Observations
- [convention] Observation categories: meaning, appearance, ambiguity, interpretation, quote, evolution
- [convention] Relations: represents, associated_with, appears_in, contrasts_with, located_at"""
)
write_note(
title="LiteraryDevice",
directory="schema",
note_type="schema",
metadata={
"entity": "LiteraryDevice",
"version": 1,
"schema": {
"description": "string, what the device is",
"device_type(enum)": "[rhetorical, structural, figurative, narrative, dramatic], category",
"frequency(enum)": "[pervasive, frequent, occasional, rare], how often used"
},
"settings": {"validation": "warn"}
},
content="""# LiteraryDevice
Schema for literary technique and device notes.
## Observations
- [convention] Observation categories: definition, usage, effect, example, significance
- [convention] Relations: used_in, characterizes, expresses, related_to"""
)
<project>/
schema/ # 6 个模式定义
chapters/ # 每个章节/部分 + 序言/后记一个笔记
characters/
major/ # 主角、反派、关键配角
minor/ # 角色有限的命名人物
themes/ # 主题分析笔记
locations/ # 场景和地点
symbols/ # 象征元素
literary-devices/ # 技巧和手法
analysis/ # 跨领域综合
tasks/ # 处理进度跟踪
在处理章节之前,为主要实体创建存根笔记,以便 [[wiki-links]] 从一开始就能解析。
为每个主要人物创建一个包含已知元数据的存根:
write_note(
title="<Character Name>",
directory="characters/major",
note_type="Character",
tags=["character", "major", "<role>"],
metadata={"role": "<role>", "description": "<brief description>"},
content="""# <Character Name>
## Observations
- [role] <Character's role in the work>
- [appearance] <Key physical description>
## Relations
- associated_with [[<Related Character>]]
- appears_in [[<Key Location>]]"""
)
在开始阅读前,识别作品的主要实体。一个好的起始清单:
| 类型 | 典型数量 | 包含内容 |
|---|---|---|
| 人物(主要) | 8-20 | 主角、反派、关键配角 |
| 主题 | 5-12 | 作品探索的核心关切 |
| 地点 | 4-10 | 主要场景、具有象征意义的地点 |
| 象征 | 4-10 | 具有多层意义的反复出现的物体、意象或母题 |
存根不需要完整——它们为 [[wiki-link]] 提供目标,并将在章节处理过程中得到丰富。
获取全文并识别章节/部分边界。对于公共领域作品,Project Gutenberg 是一个很好的来源。对于受版权保护的作品,请使用实体书或授权的数字副本。
每批处理约 10 章,以平衡深度与进度。按叙事弧或主题焦点分组:
| 批次 | 典型内容 |
|---|---|
| 1 | 开端:场景、人物介绍、世界观构建 |
| 2-3 | 上升情节:冲突确立、关系发展 |
| 4-6 | 中间部分:复杂化、转折点、主题深化 |
| 7-8 | 高潮临近:升级、启示、危机 |
| 最终 | 高潮、结局、后记 |
根据章节长度和密度调整批次大小。简短、动作密集的章节可以更大组地分批;冗长、哲学密集的章节可能需要更小的批次。
对于每个章节:
1. 仔细阅读该章节。 如果使用源文本文件,请阅读相关部分。
2. 创建章节笔记:
write_note(
title="Chapter <N> - <Title>",
directory="chapters",
note_type="Chapter",
tags=["chapter", "<arc-phase>"],
metadata={
"chapter_number": <N>,
"pov": "<narrator or POV character>",
"setting": "<primary location>",
"narrative_mode": "<mode>"
},
content="""# Chapter <N> - <Title>
## Observations
- [summary] <1-2 sentence synopsis>
- [event] <Key plot events>
- [tone] <Emotional and stylistic atmosphere>
- [technique] <Notable narrative techniques>
- [quote] "<Significant passage>"
- [significance] <Why this chapter matters to the whole>
- [foreshadowing] <Hints at future events>
## Relations
- features [[<Character>]]
- set_in [[<Location>]]
- explores [[<Theme>]]
- contains [[<Symbol>]]
- employs [[<Literary Device>]]
- follows [[Chapter <N-1> - <Previous Title>]]
- precedes [[Chapter <N+1> - <Next Title>]]"""
)
3. 丰富相关实体:
edit_note(
identifier="characters/major/<character-slug>",
operation="append",
heading="Observations",
content="""- [arc] Ch.<N>: <What happens to this character>
- [quote] "<Attributed quote>" (Ch.<N>)"""
)
4. 跟踪进度 使用 memory-tasks 技能创建一个处理任务,以便在上下文压缩后仍能保留。
| 类别 | 寻找内容 |
|---|---|
[summary] | 1-2 句章节概要 |
[event] | 关键情节事件(行动、启示、到达) |
[tone] | 情感和风格氛围 |
[technique] | 叙事创新(POV 转换、结构实验、类型融合) |
[quote] | 令人难忘或具有主题意义的段落 |
[significance] | 该章节对整体的重要性 |
[foreshadowing] | 对未来事件的暗示 |
处理每个章节时,向相关实体追加观察:
[arc] 时刻、新的 [trait] 揭示、[quote] 归属[manifestation]、[evolution] 转变[appearance]、新的 [interpretation] 角度[atmosphere]、场景中的 [significance][example]在结构化观察就位后,考虑为主要实体笔记添加解读性散文。使用 edit_note(operation="prepend") 在观察部分前添加 2-4 段批评性文章。这篇散文应该:
散文增加了结构化观察本身无法捕捉的解读质感。
所有章节处理完毕后:
对于每个主要人物,撰写一个完整的 [arc] 总结观察,涵盖他们在整个作品中的轨迹。
对于每个主题,添加 [evolution] 观察,追踪它从引入到解决的发展过程。
在结构相似的章节之间添加 parallels 和 contrasts_with 关系(例如,镜像场景、重复场景、主题呼应)。
在 analysis/ 中创建综合笔记:
write_note(
title="Narrative Structure",
directory="analysis",
note_type="note",
tags=["analysis", "structure"],
content="""# Narrative Structure
Analysis of the work's narrative architecture.
## Observations
- [structure] <Overall arc description>
- [technique] <Key narrative strategies>
...
## Relations
- analyzes [[<Protagonist>]]
- analyzes [[<Key Character>]]
- explores [[<Central Theme>]]
..."""
)
推荐的分析笔记:
在章节处理过程中,新的次要人物、地点和象征会出现。为任何出现在 3 个以上章节或承载主题重量的实体创建笔记。
# Validate each entity type
schema_validate(noteType="Character")
schema_validate(noteType="Theme")
schema_validate(noteType="Chapter")
schema_validate(noteType="Location")
schema_validate(noteType="Symbol")
schema_validate(noteType="LiteraryDevice")
schema_diff(noteType="Character")
# ... for each type
修复发现的问题——常见的修复:
edit_note 添加抽查双向关系:如果章节 X features [[Character]],那么人物是否有引用章节 X 的观察?修复空白。
生成用于可视化探索的画布文件:
# Character relationship web
canvas(query="type:Character AND role:protagonist OR role:antagonist OR role:supporting")
# Theme connections
canvas(query="type:Theme")
# Chapter timeline with key events
canvas(query="type:Chapter", layout="timeline")
此流程适用于任何文学文本。根据体裁调整模式:
| 体裁 | 模式调整 |
|---|---|
| 小说 | 基础模式按原样工作;根据需要添加体裁特定的人物字段 |
| 戏剧 | 添加 Act 和 Scene 模式;人物获得 speaking_lines 字段 |
| 诗集 | 将 Chapter 替换为 Poem;添加 form、meter、rhyme_scheme 字段 |
| 非虚构 | 将 Chapter 替换为 Section;添加 Argument、Evidence 模式 |
| 短篇小说集 | 添加 Story 模式,包含 narrator、setting、word_count |
| 史诗/神话 | 添加 Deity、Prophecy 模式;地点获得 mythological_significance |
| 回忆录 | 人物模式获得 relationship_to_narrator;添加 Memory 模式 |
| 作品长度 | 批次大小 | 预计笔记数量 |
|---|---|---|
| 中篇小说(约 4 万字) | 5-10 章 | ~50-80 |
| 小说(约 8 万字) | 8-12 章 | ~100-150 |
| 长篇小说(约 20 万字以上) | 10-15 章 | ~200-300 |
| 系列(多卷) | 每次处理一卷 | 每卷 ~200+ |
schema_validate,而不仅仅是在最后。及早发现漂移。[quote] 观察包含进来。analysis/ 中的综合笔记应在所有章节处理完毕后,当你拥有完整图景时撰写。每周安装次数
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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.
Phase 0: Setup → project, schemas, directory structure
Phase 1: Seed → stub notes for known major entities
Phase 2: Process → chapter-by-chapter notes in batches
Phase 3: Cross-ref → enrich arcs, add parallels, write analysis
Phase 4: Validate → schema checks, drift detection, consistency
Phase 5: Visualize → canvas files for character webs, timelines
create_memory_project(name="<work-name>", path="~/basic-memory/<work-name>")
Use a kebab-case slug of the work's title (e.g., great-gatsby, hamlet, beloved).
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.
write_note(
title="Character",
directory="schema",
note_type="schema",
metadata={
"entity": "Character",
"version": 1,
"schema": {
"role(enum)": "[protagonist, antagonist, supporting, minor], character's narrative role",
"description": "string, brief character description",
"first_appearance?": "string, chapter or scene of first appearance",
"status?(enum)": "[alive, dead, unknown, transformed], character status at end of work"
},
"settings": {"validation": "warn"}
},
content="""# Character
Schema for character entity notes.
## Observations
- [convention] Major characters in characters/major/, minor in characters/minor/
- [convention] Observation categories: trait, motivation, arc, quote, appearance, relationship, symbolism, fate
- [convention] Relations: appears_in, contrasts_with, allied_with, commands, symbolizes, associated_with"""
)
Add work-specific fields as needed — e.g., rank for military fiction, house for family sagas, species for fantasy.
write_note(
title="Theme",
directory="schema",
note_type="schema",
metadata={
"entity": "Theme",
"version": 1,
"schema": {
"description": "string, what this theme explores",
"prevalence(enum)": "[major, minor], how central to the work",
"first_introduced?": "string, where theme first appears"
},
"settings": {"validation": "warn"}
},
content="""# Theme
Schema for thematic analysis notes.
## Observations
- [convention] Observation categories: definition, manifestation, evolution, counterpoint, quote, interpretation
- [convention] Relations: embodied_by, contrasts_with, reinforced_by, explored_in, expressed_through"""
)
write_note(
title="Chapter",
directory="schema",
note_type="schema",
metadata={
"entity": "Chapter",
"version": 1,
"schema": {
"chapter_number": "integer, sequential chapter number",
"pov?": "string, point-of-view character or narrator mode",
"setting?": "string, primary location",
"narrative_mode?(enum)": "[dramatic, expository, reflective, epistolary, mixed], chapter's primary mode"
},
"settings": {"validation": "warn"}
},
content="""# Chapter
Schema for chapter-level analysis notes.
## Observations
- [convention] Chapters stored in chapters/ directory
- [convention] Observation categories: summary, event, tone, technique, quote, significance, foreshadowing
- [convention] Relations: features, set_in, explores, contains, employs, follows, precedes, parallels"""
)
write_note(
title="Location",
directory="schema",
note_type="schema",
metadata={
"entity": "Location",
"version": 1,
"schema": {
"description": "string, what this place is",
"location_type(enum)": "[city, building, landscape, body_of_water, region, fictional, vehicle], type of place",
"real_or_fictional(enum)": "[real, fictional, both], whether the place exists"
},
"settings": {"validation": "warn"}
},
content="""# Location
Schema for location and setting notes.
## Observations
- [convention] Observation categories: description, atmosphere, symbolism, significance, geography
- [convention] Relations: setting_for, associated_with, symbolizes, contains, part_of"""
)
write_note(
title="Symbol",
directory="schema",
note_type="schema",
metadata={
"entity": "Symbol",
"version": 1,
"schema": {
"description": "string, what the symbol is literally",
"symbol_type(enum)": "[object, animal, color, action, natural_phenomenon, body_part], category of symbol",
"primary_meaning": "string, most common interpretation"
},
"settings": {"validation": "warn"}
},
content="""# Symbol
Schema for symbolic element notes.
## Observations
- [convention] Observation categories: meaning, appearance, ambiguity, interpretation, quote, evolution
- [convention] Relations: represents, associated_with, appears_in, contrasts_with, located_at"""
)
write_note(
title="LiteraryDevice",
directory="schema",
note_type="schema",
metadata={
"entity": "LiteraryDevice",
"version": 1,
"schema": {
"description": "string, what the device is",
"device_type(enum)": "[rhetorical, structural, figurative, narrative, dramatic], category",
"frequency(enum)": "[pervasive, frequent, occasional, rare], how often used"
},
"settings": {"validation": "warn"}
},
content="""# LiteraryDevice
Schema for literary technique and device notes.
## Observations
- [convention] Observation categories: definition, usage, effect, example, significance
- [convention] Relations: used_in, characterizes, expresses, related_to"""
)
<project>/
schema/ # 6 schema definitions
chapters/ # one note per chapter/section + prologue/epilogue
characters/
major/ # protagonist, antagonist, key supporting
minor/ # named characters with limited roles
themes/ # thematic analysis notes
locations/ # settings and places
symbols/ # symbolic elements
literary-devices/ # techniques and devices
analysis/ # cross-cutting synthesis
tasks/ # processing tracker
Before processing chapters, create stub notes for major entities so [[wiki-links]] resolve from the start.
For each major character, create a stub with known metadata:
write_note(
title="<Character Name>",
directory="characters/major",
note_type="Character",
tags=["character", "major", "<role>"],
metadata={"role": "<role>", "description": "<brief description>"},
content="""# <Character Name>
## Observations
- [role] <Character's role in the work>
- [appearance] <Key physical description>
## Relations
- associated_with [[<Related Character>]]
- appears_in [[<Key Location>]]"""
)
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.
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.
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.
For each chapter:
1. Read the chapter carefully. If working from a source text file, read the relevant section.
2. Create the chapter note:
write_note(
title="Chapter <N> - <Title>",
directory="chapters",
note_type="Chapter",
tags=["chapter", "<arc-phase>"],
metadata={
"chapter_number": <N>,
"pov": "<narrator or POV character>",
"setting": "<primary location>",
"narrative_mode": "<mode>"
},
content="""# Chapter <N> - <Title>
## Observations
- [summary] <1-2 sentence synopsis>
- [event] <Key plot events>
- [tone] <Emotional and stylistic atmosphere>
- [technique] <Notable narrative techniques>
- [quote] "<Significant passage>"
- [significance] <Why this chapter matters to the whole>
- [foreshadowing] <Hints at future events>
## Relations
- features [[<Character>]]
- set_in [[<Location>]]
- explores [[<Theme>]]
- contains [[<Symbol>]]
- employs [[<Literary Device>]]
- follows [[Chapter <N-1> - <Previous Title>]]
- precedes [[Chapter <N+1> - <Next Title>]]"""
)
3. Enrich related entities:
edit_note(
identifier="characters/major/<character-slug>",
operation="append",
heading="Observations",
content="""- [arc] Ch.<N>: <What happens to this character>
- [quote] "<Attributed quote>" (Ch.<N>)"""
)
4. Track progress using the memory-tasks skill to create a processing task that survives context compaction.
| 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] |
As each chapter is processed, append observations to relevant entities:
[arc] moments, new [trait] revelations, [quote] attributions[manifestation] in this chapter, [evolution] shifts[appearance] with context, new [interpretation] angles[atmosphere] as described, [significance] in sceneAfter 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:
The prose adds the interpretive texture that structured observations alone cannot capture.
After all chapters are processed:
For each major character, write a full [arc] summary observation covering their trajectory across the work.
For each theme, add [evolution] observations tracing how it develops from introduction to resolution.
Add parallels and contrasts_with relations between structurally similar chapters (e.g., mirrored scenes, repeated settings, thematic echoes).
Create synthesis notes in analysis/:
write_note(
title="Narrative Structure",
directory="analysis",
note_type="note",
tags=["analysis", "structure"],
content="""# Narrative Structure
Analysis of the work's narrative architecture.
## Observations
- [structure] <Overall arc description>
- [technique] <Key narrative strategies>
...
## Relations
- analyzes [[<Protagonist>]]
- analyzes [[<Key Character>]]
- explores [[<Central Theme>]]
..."""
)
Recommended analysis notes:
During chapter processing, new minor characters, locations, and symbols will emerge. Create notes for any that appear in 3+ chapters or carry thematic weight.
# Validate each entity type
schema_validate(noteType="Character")
schema_validate(noteType="Theme")
schema_validate(noteType="Chapter")
schema_validate(noteType="Location")
schema_validate(noteType="Symbol")
schema_validate(noteType="LiteraryDevice")
schema_diff(noteType="Character")
# ... for each type
Fix issues found — common fixes:
edit_noteSpot-check bidirectional relations: if Chapter X features [[Character]], does Character have observations referencing Chapter X? Fix gaps.
Generate canvas files for visual exploration:
# Character relationship web
canvas(query="type:Character AND role:protagonist OR role:antagonist OR role:supporting")
# Theme connections
canvas(query="type:Theme")
# Chapter timeline with key events
canvas(query="type:Chapter", layout="timeline")
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 |
| 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 |
schema_validate after each batch, not just at the end. Catch drift early.[quote] observations with chapter attribution.Weekly Installs
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Excel财务建模规范与xlsx文件处理指南:专业格式、零错误公式与数据分析
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| Why this chapter matters to the whole |
[foreshadowing] | Hints at future events |
[example]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 |
analysis/