Analysis To Vault

Analysis Article → Vault

One long-form analytical article in, four artifacts out: thesis-and-arguments note + compressed cheatsheet + Kanban task injection + mindmap extension. Designed for 行业长文 / 深度解析 / editorial / 公司研究 that argues a thesis rather than teaching procedures.

When to use this skill (and when NOT to)

Use this skill when the source is:

• 行业分析长文 (e.g. "深度解析 FDE 数据特种兵") — argues a thesis with multiple supporting sections
• Editorial / opinion piece — has a clear stance, not neutral reporting
• Company deep-dive — Palantir / OpenAI / Anthropic-style essays
• Person profile / founder story — argues "this person is interesting because X"
• Trend analysis — argues "AI/产业 is shifting in direction Y"
• Research summary — not a paper, but a journalist's synthesis of multiple findings

Do NOT use this skill when:

• The source is a book chapter (use book-chapter-to-vault — that skill assumes "金句 → 复述题" structure)
• The source is a research paper (use a paper skill)
• The source is a short blog post / Twitter thread (just write the note directly)
• The user wants a public-facing summary (use wechat-article-pack for WeChat, or just write the summary)
• The source is purely descriptive with no thesis (e.g. a how-to tutorial — that's a chapter, use the other skill)

How this skill differs from book-chapter-to-vault

The two skills share the same philosophy (active recall, scannable, kanban/mindmap integration) but have different decomposition templates because chapters and essays have different information shapes.

Inputs

Before starting, confirm with the user:

1. Source path — .docx or already-extracted .md
2. Output directory — the personal learning vault
3. Existing artifacts to extend — kanban + mindmap paths (optional)
4. Day-job context (CRITICAL) — unlike a generic book chapter, analytical articles need a "what does this mean for YOU" pass. Ask the user: "What's your main work focus? I'll tailor the day-job implications section to that."

Outputs

For a single article, the skill produces:

<vault>/
├── notes/
│   ├── <slug>.md              # per-article thesis-and-arguments note
│   └── cheatsheet-all.md      # regenerated, one A4 page
├── kanban/kanban.md           # extended with new sub-section in Backlog
└── mindmap/技能树.md          # extended with new branch

The 6-step playbook

Step 1 — Extract

Use the same extract_docx.py from FDE/book-chapter-to-vault/scripts/. Long essays usually have fewer headings than chapters, so headings may be sparse — that's OK, you'll be decomposing by argument, not by sub-section.

Step 2 — Read once for the central thesis

Read the whole thing once (or skim 3 randomly-chosen sections) and write down one sentence that captures the article's central thesis. If you can't, the article probably doesn't have a clear thesis — either ask the user "what's the takeaway you want me to extract?" or downgrade the source to a "summary" rather than a "thesis-driven note."

A good central thesis has:

• A claim (not a topic)
• A subject (the entity being claimed about)
• An implication (why the claim matters)

Examples:

• ❌ "This article is about FDE" (topic, not thesis)
• ✅ "FDE exists because 95% of AI projects fail at the integration step, and FDE is the role that fills that gap" (claim + subject + implication)

Step 3 — Build the argument map (6-10 arguments)

For each main section, identify:

• What claim does this section make? (1 sentence)
• What evidence supports it? (data, case study, quote from expert, comparison)
• Is this argument load-bearing or decorative? (load-bearing = removing it would break the thesis; decorative = nice to have but the thesis stands without it)

If the article has < 6 load-bearing arguments, you may have misidentified the thesis. If > 10, look for clusters — 3 arguments that all support the same super-claim should be one argument with sub-points.

For each argument, write to your draft:

论点 N · <Argument name>
> 原文：「<the actual claim, in the source's words>」
我的理解：<1-3 sentences in your own words>
论据 / 数据：<the evidence, with attribution>
呼应论点：<how it relates to other arguments in this article>  (optional)
Day-job 启示：<1 sentence on what this means for the user>

Step 4 — Extract key data points

Make a single table of all data points, names, and concrete facts mentioned in the article. This is the "citation index" — the user will use it later when citing the article in their own work.

Format:

5-15 rows. If a fact is decorative, drop it. If a fact is load-bearing (the argument falls apart without it), keep it and bold it.

Step 5 — Write the per-article note

Use references/article-template.md as the template. Structure:

# <Article Title>

> 中心论点（1 句话）

## 📑 文章地图
| 节 | 主题 | 关键产出 |

## 🧠 核心论点（N 个）
### 论点 1 · <Name>
> 原文
我的理解
论据 / 数据
Day-job 启示

## 📊 关键数据 / 事实表

## 🔄 与其他材料的呼应

## 💡 对 Day-Job 的启示

## ❓ 待探索的问题（Open Questions）

## 🧪 Self-Test

## 📎 关键金句

## 🔗 相关章节 / 资源

Step 6 — Inject into cheatsheet / kanban / mindmap

Cheatsheet: extend with a new section. Use the compressed version — not the full note. If the cheatsheet is already 4000+ chars, demote less critical points to the per-article note.

Kanban: add a new sub-section 🆕 <article title> 衍生（<date> 增） with 3-5 D-items. D-items for analytical articles are strategic (this quarter) not operational (this week). E.g.:

• "Find the MIT 2025 95% report and read it"
• "Build a minimal Ontology layer for current POC"
• "Audit my last 3 POCs against the 'quantified metric' rule"

Mindmap: extend the existing branch with a new sub-branch. For FDE-related content, the branch goes under 📘 FDE 实战圣经 (or create a new top-level if the article is from a different tradition).

Quality bar (acceptance criteria)

• The central thesis is one sentence with a clear claim + subject + implication.
• The argument map has 6-10 load-bearing arguments (not all sub-sections — cluster weak ones).
• Each argument has evidence attribution (which source/quote/data supports it).
• The data table has 5-15 entries with category + fact + source.
• The "Day-job implications" section is specific to the user (not generic advice).
• The "Open Questions" section lists 3-6 things the article raised but didn't answer.
• The cheatsheet fits in one A4 page (≤ 4000-4500 chars).
• The kanban D-items are strategic (not operational — those are chapter-style).
• The mindmap branch is in the right place (matches the article's domain).
• The note's "我的理解" / "Day-job 启示" is in your own words, not paraphrased.

Reusability — what makes this skill portable

• The article template is domain-agnostic. Works for tech industry analysis, business essays, founder profiles, trend pieces.
• The thesis-extraction discipline is the most valuable habit — once you force yourself to write the central thesis in one sentence, the rest of the analysis organizes itself.
• The argument map generalizes — any "X is happening because Y" essay maps to the same template.
• The data table is a citation index — use it for any future writing that cites this article.

Known limitations

• Opinion-heavy articles (e.g. "Why X is the future") may have thin evidence — the data table will be sparse. That's OK, note it and downgrade the "Day-job 启示" to "this is a strong opinion, treat as a hypothesis."
• Multi-author articles or panel-style essays may not have a single thesis — fall back to a "summary of positions" structure instead of a thesis-and-arguments structure.
• Articles in a foreign language with domain jargon (e.g. "Transformer 的涌现能力") may need a glossary in the note. Add a 5-10 row "术语表" if needed.
• The day-job section requires user input. Unlike chapters, where day-job 启示 can be generic, analytical articles need a specific user context to be useful. Always ask before writing this section.

Worked example

See examples/deep-analysis-fde/ for the actual output of running this skill on the article "深度解析 FDE：年薪百万的'数据特种兵'如何打通 AI 落地最后一公里". This is the canonical reference for "what good output looks like."

The example demonstrates:

• A clear 1-sentence central thesis (95% AI 项目失败 → 缺翻译的人 → FDE 存在)
• 10 arguments mapped to the article's 10 sections (with some clustering where appropriate)
• 11-row data table (薪酬/风险/案例/效率/人才/中国)
• Day-job implications section tailored to the user's "LLM-on-Mac" day-job context

Reference index

• references/article-template.md — the per-article note template
• references/argument-map-template.md — the thesis + argument decomposition template
• references/cross-reference-template.md — how to link this article to other notes in the vault
• references/cheatsheet-extension.md — how to extend the existing cheatsheet
• examples/deep-analysis-fde/notes/ — the actual output of running this skill

Dependency

• Reuses ../book-chapter-to-vault/scripts/extract_docx.py for the .docx → .md extraction. No additional scripts needed.