How `BOOK_OVERVIEW.md` Is Generated by Adler Analysis in cangjie-skill

BOOK_OVERVIEW.md is generated by a four-step Adler analysis pipeline—Structural, Interpretive, Critical, and Applicability—that collects metadata, answers LLM-driven checklists, and renders results into a Jinja2 template.

The cangjie-skill repository implements this process in Stage 0 of its knowledge-extraction pipeline. According to the source code in methodology/01-stage0-adler.md, the system transforms raw source material into a structured global context document that downstream modules consume for book-level comprehension tasks.

The Four Steps of Adler Analysis

The Adler analysis stage follows Mortimer Adler's analytical reading framework. As implemented in kangarooking/cangjie-skill, each step produces specific outputs that feed into the final template.

1. Structural Analysis

The first step establishes the book's architecture. The LLM answers checklist items including:

• "What is the one-sentence purpose?"
• "List the 3-7 primary arguments"
• Identify the organizational pattern (并列 / 递进 / 对比 / 反驳 / 层层深入)

This structural skeleton becomes the foundation for all subsequent analysis.

2. Interpretive Analysis

The second step extracts semantic content. Key outputs include:

• Terminology dictionary: Core concepts with author-specific definitions
• Propositions: Explicit claims made by the author
• Argument chains: How the author connects evidence to conclusions

The methodology file specifies that this step must distinguish between the author's definitions and common usage (see {{author's definition}} vs. {{what's different}} placeholders in the template).

3. Critical Analysis

The third step evaluates the work's reliability and boundaries:

• Author's era-specific limitations (作者的时代局限)
• Ideological blind spots (作者的立场盲点)
• Unproven assumptions
• Valid counter-arguments

These critical markers prevent downstream modules from uncritically accepting all claims.

4. Applicability Analysis

The final step bridges theory to practice by identifying:

• Candidate skill themes (候选主题 1, 候选主题 2...)
• Priority ranking (top priority)
• Implementation difficulty estimates (N)

This step ensures the extracted knowledge serves practical skill-acquisition goals.

Template Rendering Pipeline

After the four-step analysis completes, the system renders answers into templates/BOOK_OVERVIEW.md.template. The template contains bilingual placeholders such as {{BOOK_TITLE}}, {{AUTHOR}}, {{YEAR}}, {{论点 1}}, {{term}}, and {{作者的时代局限}}.

Rendering Implementation

The actual rendering uses Jinja2-style substitution. Below is a minimal reconstruction of the pipeline logic:

import json
from pathlib import Path
from jinja2 import Template

# Load the template from cangjie-skill repository

template_path = Path(
    "/cache/repos/github.com/kangarooking/cangjie-skill/main/templates/BOOK_OVERVIEW.md.template"
)
template = Template(template_path.read_text(encoding="utf-8"))

# Adler analysis produces this answer dictionary

adler_answers = {
    "BOOK_TITLE": "Deep Work",
    "AUTHOR": "Cal Newport",
    "YEAR": "2016",
    "SOURCE_FILE": "deep_work.pdf",
    "DATE": "2026-08-15",
    # Structural outputs

    "方法论 / 传记 / 哲学 / 实操手册 / ...": "实操手册",
    "一句话主旨": "专注是提升认知产出的唯一途径",
    "论点 1": "深度工作的定义",
    "论点 2": "深度工作的价值",
    "论点 3": "培养深度工作的方法",
    "并列 / 递进 / 对比 / 反驳 / 层层深入": "递进",
    "作者要解决的核心问题": "如何在信息碎片化的时代保持高效产出",
    # Interpretive outputs

    "term": "深度工作",
    "author's definition": "在没有干扰的状态下进行的专业活动",
    "what's different": "与“忙碌”不同，它产生实际价值",
    "命题 1": "深度工作能够显著提升技能水平",
    "命题 2": "浅度工作无法带来同等回报",
    "论证链": "通过案例、研究数据与逻辑推演说明上述命题",
    # Critical outputs

    "作者的时代局限": "缺少对 AI 辅助工具的深度讨论",
    "作者的立场盲点": "假设所有人都有高度自律的工作环境",
    "未被证明的假设": "深度工作一定能提升收入",
    "反对意见": "在某些创意行业浅度工作更有价值",
    # Applicability outputs

    "候选主题 1": "时间块管理法",
    "候选主题 2": "注意力排除技巧",
    "N": "5",
    "top priority": "时间块管理法",
}

# Render and write the final markdown

rendered_md = template.render(**adler_answers)

output_path = Path("/tmp/books/deep-work/BOOK_OVERVIEW.md")
output_path.parent.mkdir(parents=True, exist_ok=True)
output_path.write_text(rendered_md, encoding="utf-8")

Key pipeline stages:

• Template loading: Matches templates/BOOK_OVERVIEW.md.template structure exactly
• Answer population: Represents LLM-generated responses from the four Adler steps (lines 11-44 of 01-stage0-adler.md)
• Placeholder substitution: template.render() performs the transformation
• File output: Writes to books/<slug>/BOOK_OVERVIEW.md as declared in line 7 of the Adler methodology file

Output Location and Downstream Usage

The generated file follows a consistent path convention. As specified in methodology/01-stage0-adler.md line 7 and referenced in SKILL.md line 23 and README.en.md line 45:

books/<slug>/BOOK_OVERVIEW.md

This file serves as global context for every subsequent pipeline stage. According to methodology/07-stage5-deliver.md, downstream extractors and skill modules import BOOK_OVERVIEW.md to access:

• Structural skeleton for navigation
• Terminology dictionary for consistent interpretation
• Critical observations for quality control
• Applicability notes for practical implementation

Without this centralized context document, later stages would lack book-level coherence in their extractions.

Source Files in cangjie-skill

File	Purpose
methodology/01-stage0-adler.md	Defines the four Adler steps and expected outputs
templates/BOOK_OVERVIEW.md.template	Jinja2 template with bilingual placeholders
SKILL.md	Pipeline overview confirming Stage 0 outputs
README.en.md	User-facing documentation of the Adler analysis stage
methodology/07-stage5-deliver.md	Explains global context consumption

Summary

• Four-step framework: Structural → Interpretive → Critical → Applicability analysis as defined in methodology/01-stage0-adler.md
• LLM-driven extraction: Checklist-based Q&A generates structured answers for each step
• Template rendering: Jinja2 substitution populates templates/BOOK_OVERVIEW.md.template
• Standardized output: Written to books/<slug>/BOOK_OVERVIEW.md per line 7 of the Adler methodology
• Global context role: Consumed by all downstream stages for book-level coherence

Frequently Asked Questions

What makes the Adler analysis in cangjie-skill different from standard book summaries?

The cangjie-skill Adler analysis enforces systematic critical evaluation through its four-step structure. Unlike generic summaries, it requires explicit identification of author limitations, unproven assumptions, and applicability trade-offs—elements specified in the 作者的时代局限 and 未被证明的假设 fields of the template.

Can the template placeholders be customized for different source types?

The current templates/BOOK_OVERVIEW.md.template uses fixed bilingual placeholders, but the methodology in 01-stage0-adler.md is source-agnostic. The four-step framework adapts to methodology books, biographies, philosophy texts, or practical manuals (实操手册) through the same structural → interpretive → critical → applicability progression.

How does BOOK_OVERVIEW.md differ from stage-specific outputs?

While later stages produce focused extracts (skills, flashcards, checklists), BOOK_OVERVIEW.md remains the only document with complete book-level context. This design prevents fragmentation—downstream agents reference the overview rather than re-analyzing source material, as documented in methodology/07-stage5-deliver.md.

Where is the actual LLM prompting logic located?

The specific prompts that drive the four Adler steps are embedded in methodology/01-stage0-adler.md lines 11-44. These prompts include explicit checklist items ("What is the one-sentence purpose?", "List the 3-7 primary arguments") that constrain LLM outputs to match the template's expected fields.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}