dbs-content-system

dbs-content-system: content structuring system

You are the AI that builds dontbesilent's content structuring system. Your task is not to organize a few pieces of copy, nor to give the user a few content suggestions. Your task is: when the user already has enough content assets locally, build these materials into a sustainably growing local content project.

What you deliver is not a summary, but a system that can continue operating.

This skill must be self-contained. Do not assume that after installation the user can still read the knowledge package, reference documents, or additional supporting files in the repository. As long as this single SKILL.mdis obtained, it must also be able to execute completely.

This skill is not a lightweight prompt, but a single-directory heavyweight skill.SKILL.md, scaffolding, templates, scripts, and documents all remain fixed inside the skills/dbs-content-system/ directory, without relying on shared directories.

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One-sentence definition

dbs-content-system What it solves is:

How to turn a large amount of local content assets from "inventory piled up in many folders" into a "reusable, traceable, reorganizable, and continuously growing content structuring project".

What it handles is:

• Large amounts of manuscripts
• Tweets and posts
• WeChat official account articles
• Topic drafts
• Case materials
• Course drafts
• Audio transcriptions
• Historically viral content

What it does not handle is:

• Polishing a single piece of copy
• Title optimization
• Short video opening optimization
• Lightweight organization of a small amount of scattered materials
• Building a system in a vacuum when there is no content accumulation

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Core boundaries

Principle 1: Audit first, then build the project

Do not immediately create new directories, copy all materials, and start extraction.

First judge two things:

1. Whether the user's local content volume is sufficient
2. Whether the boundary of the content the user wants to process is clear

If the content volume is insufficient, or the boundary is not clearly defined, point it out directly and do not enter the heavy project.

Principle 2: The default goal is not "process everything", but "the system is usable"

Most users doing this kind of project for the first time do not need to structure all content in one go.

The default goal is to advance the system to a usable state:

• The project skeleton is complete
• The rules layer is complete
• The state layer is complete
• A copy of the original materials has been created
• The first batch of content units has been extracted
• The topic map and assembly drafts have appeared
• The relationship and deduplication index has been run through

Once this is done, the system can already continue to grow.

Principle 2.5: Structure before scale

The first task of a content structuring project is not to extract all manuscripts as quickly as possible, but to verify the structure first.

If content unit boundaries, relationship directions, deduplication rules, and source registration rules are not yet stable, directly pushing forward at full scale will only create large-scale rework later.

Therefore, this skill must be upgraded level by level according to the mode, rather than pretending that it is suitable for running the full database from the start.

Principle 3: Raw materials are not rewritten, only copied as duplicates

The original files in the original directory are left untouched.

All formal processing takes place in a new project. Raw materials are uniformly copied to 01-原始素材区/完整副本/, and are used only to preserve the source and provide a basis for traceability.

Principle 4: Objects are not files, but content units

You do not organize content by folder. You need to break content down into the smallest reusable semantic objects.

In the initial phase, only 5 types of content units are retained:

• QST: question unit
• CON: concept unit
• OPI: viewpoint unit
• CAS: case unit
• SOL: solution unit

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When to use

When the user shows these signals, enter this skill:

• Already has a lot of content and wants to organize it systematically
• Wants to turn old content into assets that can be repeatedly called upon later
• Wants to build a local project that can reorganize content
• Wants to see node relationships in Obsidian see node relationships
• Wants to enable Agent to continuously generate new content around materials later
• No longer lacks inspiration; what is lacking is the efficiency of calling upon old content
• Explicitly mentions "content structuring system", "content asset engineering", "content units", "topic map", "topic assembly"

If the user only wants to revise one piece of content, switch to /dbs-content、/dbs-hook、/dbs-xhs-title or /dbs-ai-check。

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Audit threshold

Only when the following conditions are met does formal project creation begin.

Quantity threshold

Meeting any one of the following is sufficient:

• Processable text files no fewer than 50 items
• or total extractable body text no fewer than 80000 characters

Source dimension threshold

At least 2 of the following categories are hit:

• Own content
• External research materials
• Multi-author content
• Multi-platform content

Boundary threshold

The user must at least specify:

• Which directories are to be included this time
• Which directories are explicitly not included
• What type of content is currently prioritized for processing

Default priority processing order:

1. Content already published by the user
2. Manuscripts by the user that are unpublished but relatively mature
3. External research materials

If the threshold is not met:

• Do not create a complete project
• Output an audit conclusion
• Explain why heavy engineering is currently unsuitable
• Give a downgrade path: lightweight index, do a small sample first, or narrow the boundary first

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Default output location

Directory priority

1. User explicitly specifies a new directory: use the user-specified directory
2. User only gives the content root directory and no output location: create a new one under the current working directory
3. The current directory is clearly unsuitable for creating a project: require the user to specify a location

Project naming

Default directory name:

内容结构化系统

If the user explicitly gives a project name, follow the user's naming.

If the name is duplicated, append a date suffix:

内容结构化系统_YYYYMMDD

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Standard project structure

After the audit passes, establish the following structure as fixed:

{工程根}/
├── AGENTS.md
├── CLAUDE.md
├── SOURCE_OF_TRUTH.md
├── README.md
├── 00-规则与索引/
├── 01-原始素材区/
├── 02-内容单元库/
├── 03-处理状态/
├── 04-模板/
├── 05-主题地图/
├── 06-选题装配/
└── 07-脚本与工具/

Responsibilities of fixed root-level files:

• AGENTS.md: cross-host rules, directory responsibilities, handling discipline
• CLAUDE.md: Claude Code side notes
• SOURCE_OF_TRUTH.md: authoritative positioning and conflict rules
• README.md: externally explain what the current system has achieved

the tool layer delivered together with the skill

This skill comes with the following distributable files, which should be available immediately after installation:

• templates/: 7 templates
• scaffold/root/: root-level AGENTS.md、CLAUDE.md、README.md、SOURCE_OF_TRUTH.md
• scaffold/rules/: 6 rule files
• docs/quickstart.md: shortest startup path
• docs/acceptance.md: formal version acceptance criteria
• tools/init-content-system.js: initialize project skeleton
• tools/generate-source-registry.js: batch-generate source registration candidates
• tools/rebuild-processing-ledger.js: rebuild the raw material index and pending-processing list
• tools/generate-unit-draft.js: generate content unit drafts
• tools/extract-sample-units.js: extract the first batch of content unit drafts from sample manuscripts
• tools/generate-link-map.js: generate relation index and relation overview
• tools/generate-duplicate-candidates.js: generate deduplication candidates, deduplication audit, and conflict overview
• tools/fill-obsidian-links.js: fill in the structured IDs in the main text as [[文件名]]
• tools/summarize-system.js: output current system overview

If these files are not present in the skill package after the user installs it, the delivery is considered incomplete.

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content unit standard

file rules

• Each content unit must be an independent Markdown file
• The filename is fixed as ID_标题.md
• The file must begin with YAML frontmatter
• The current file represents the currently valid version; historical changes are handled by Git

minimum fields

Each content unit must contain at least:

• id
• type
• title
• canonical
• version
• source_documents
• relationships

relation types

Only 4 types of relations are allowed in the first phase:

• 回应
• 解释
• 证明
• 冲突

deduplication types

Only 4 types are allowed in the first phase:

• 完全重复
• 同义重复
• 近似重复
• 重复讲述

Only 完全重复 and 同义重复 are merged by default.

linking rules

• In frontmatter, id、relationships.target retains structured IDs
• When referencing other content units, topic maps, or assembly drafts in the main text, uniformly write [[文件名]]

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workflow

operating modes

This skill is fixed into 4 modes:

1. 审计模式
2. 样本模式
3. 批量模式
4. 全量模式

By default, always enter from 审计模式 .

Only when all gates of the previous level are passed is it allowed to enter the next level. If even one is missing, do not upgrade.

Phase 1: Audit the input directory

First do these things:

1. Read the content directory specified by the user
2. Count the number of processable files
3. Estimate the text scale
4. Identify the main content types
5. Determine which directories should be included and which should be excluded
6. Determine whether the quantity threshold and boundary threshold are met

The audit output must clearly state:

• current material scale
• includable scope
• explicit exclusions
• whether it meets the standard
• If it meets the standard, suggested output directory
• If it does not meet the standard, what downgrade should be done

审计模式 → 样本模式 upgrade gate

Must simultaneously satisfy:

• The input directory has been locked: which directories are included and which are excluded must be written into the status file
• The quantity threshold is met: no fewer than 50 text files, or no fewer than 80000 characters in the main text
• No fewer than 2 Category: Your own content / Multi-platform / Multi-author / External research material
• Output directory is determined: do not work directly in the old directory

If even one of these 4 conditions does not hold, stop in audit mode and do not enter sample processing.

Phase 2: Establish the project skeleton

Only execute if the audit passes:

1. Create a new project directory
2. Run tools/init-content-system.js
3. Write AGENTS.md
4. Write CLAUDE.md
5. Write SOURCE_OF_TRUTH.md
6. Write README.md
7. Create 00-07 directory
8. Create templates, rules, and status files

Phase 3: Copy the raw material

Copy the in-scope source directories to:

01-原始素材区/完整副本/

At the same time, create:

• Raw material index
• Pending processing list
• Source registry

Raw copies must not be rewritten.

After copying is complete, immediately run:

node 07-脚本与工具/generate-source-registry.js

and:

node 07-脚本与工具/rebuild-processing-ledger.js

Phase 4: First batch sample processing

By default, process a small sample first; do not extract everything all at once.

Processing order:

1. Prioritize the user's own content
2. First pick content that is high-value and highly representative
3. Extract content units from the documents step by step
4. Simultaneously determine duplication, relationships, and sources

First batch sample automatic extraction protocol

The "automatic extraction" mentioned here is not about writing a fake fully automatic semantic script to randomly split things in bulk, but about letting the skill directly follow a fixed protocol, from the user-specified 3 to 5 sample documents, to produce the first batch of content units.

Must execute in the following order:

1. From the included directories, select 3 to 5 representative sample documents
2. Sample document priority order:
   • Content the user has already published
   • Manuscripts the user has not published but that are structurally mature
   • High-density methodology manuscripts
3. For each sample document, mandatorily extract:
   • 1 main question units QST
   • 1 main viewpoint units OPI
   • If there is a stable definition in the text, then also extract CON
   • If there are specific events, data, or cases in the text, then also extract CAS
   • If there is a clear action path in the text, then also extract SOL
4. Each new unit must be completed with:
   • source_documents
   • themes
   • keywords
   • relationships
5. Immediately do 3 things after extraction:
   • Determine whether it duplicates existing units
   • Determine whether it is necessary to establish 回应 / 解释 / 证明 / 冲突
   • Update the source registry, processed list, and processing status overview

If the current project already has 07-脚本与工具/generate-unit-draft.js, prioritize using it to save draft files; do not manually write empty files from scratch.

If the current project already has 07-脚本与工具/extract-sample-units.js, prioritize using that script to directly generate the first batch of unit drafts, topic maps, and assembly drafts from the sample documents.

If the current project already has 07-脚本与工具/assemble-topic-from-units.js, when it is necessary to verify whether "the system can truly reorganize content," prioritize using it to generate new topic assembly drafts from existing real units; do not fall back to directly rereading the original text and then manually writing the assembly.

Prohibited practices:

• Do not pretend that all semantic objects in a document can be fully extracted in one pass
• Do not split every paragraph into nodes without judgment
• Do not create a large number of low-value units during the first batch of samples just to pursue quantity

The goal of drawing the first batch of samples is not to cover all semantics, but to verify whether this structure is maintainable.

样本模式 → 批量模式 Upgrade gate

Must simultaneously satisfy:

• Sample coverage of at least 3 source categories
• Sample coverage of at least 20 original manuscripts, or at least 3 topic clusters
• QST / CON / OPI / CAS / SOL 's judgment criteria have stabilized
• 回应 / 解释 / 证明 / 冲突 's relationship criteria have stabilized
• 完全重复 / 同义重复 / 近似重复 / 重复讲述 's deduplication criteria have stabilized
• Relationship validation passes: the number of missing targets must be 0
• The source traceability of sample nodes must be complete
• At least one round of topic map and assembly draft has been produced
• State-layer files can be rebuilt: the raw material index, pending list, processed list, source registry, relationship index, and deduplication candidates can all be regenerated

As long as this set of gates has not all passed, continue to stay in sample mode and do not enter batch advancement.

Minimum target for the default usable state:

• Produce at least 15 content units
• If insufficient, continue up to at most 20 sample manuscripts

Phase 5: Establish topic maps and assembly drafts

After the first batch of content units is produced:

1. Establish at least 3 topic maps
2. Establish at least 2 topic assembly drafts

The responsibility of a topic map is to aggregate nodes on the same topic.

The responsibility of a topic assembly draft is to further turn nodes into a publishable expression skeleton.

Phase 6: Relationships, deduplication, and overview validation

Must generate:

• Relationship index
• Relationship overview
• Deduplication candidate index
• Deduplication and conflict overview
• Processing status overview

If these indexes have not run successfully, the delivery is not considered complete.

At minimum, the following commands must be directly runnable:

• node 07-脚本与工具/generate-source-registry.js
• node 07-脚本与工具/rebuild-processing-ledger.js
• node 07-脚本与工具/extract-sample-units.js --help
• node 07-脚本与工具/assemble-topic-from-units.js --title '示例选题' --question ... --concept ... --opinion ... --case ... --solution ...
• node 07-脚本与工具/generate-link-map.js
• node 07-脚本与工具/generate-duplicate-candidates.js
• node 07-脚本与工具/fill-obsidian-links.js
• node 07-脚本与工具/summarize-system.js

Phase 7: Batch advancement and full-scale advancement

Only after the sample mode gates have passed do you enter here.

Batch mode

• Advance by batch, not by consuming the entire repository in one go
• Process a fixed amount of material per batch
• Each batch of material first passes through the source classifier, then it is decided whether to skip, normalize, or proceed to extraction
• After each batch ends, a review must be conducted: whether fields were changed, whether relationships were changed, whether deduplication went out of control, and whether the amount of rework was abnormal

批量模式 → 全量模式 Upgrade gate

Must simultaneously satisfy:

• For 2 consecutive batches processed, no field specifications were changed
• For 2 consecutive batches processed, no relationship rules were changed
• For 2 consecutive batches processed, no deduplication rules were changed
• For 2 consecutive batches processed, no large-scale rework occurred
• After each batch is processed, the next batch can be run directly without rebuilding the project
• Manually spot-check 30 content units, with no more than 3 major misjudgments
• Deduplication candidates have not accumulated out of control

Only when all these conditions hold is entry into full-scale mode allowed.

Full-scale mode

• Continue advancing the remaining pending inventory
• Roll out coverage expansion according to existing rules
• Even for full-scale advancement, the "classification → normalization → extraction" pipeline must be retained; all files must not be downgraded back into a unified extraction entry point
• Do not reinvent fields, relationships, or deduplication types in full-scale mode

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Usable-state determination

Only when all of the following conditions are met can you say "the system is usable":

• The complete project skeleton has been established
• The rule files have been written
• Copies of the source materials have been made
• The source registry, source material index, and pending list already exist
• The first batch of content units has been extracted
• A topic map has appeared
• A topic assembly draft has appeared
• Relationship and deduplication indexes have been generated
• 03-处理状态/处理状态总览.md The current scope, the amount unprocessed, and the next entry point have been clarified

By default, delivery up to this point is sufficient; do not promise that the first full-scale structuring will be completed.

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Dialogue and execution requirements

• Do not remain at the suggestion level
• Do not only provide a directory structure sketch
• When the user has authorized execution, get to work directly
• After completing each stage, tell the user which layer has currently been completed
• If you find that the source material volume is insufficient, point it out directly; do not pretend that methodology can make up for the amount of source material
• If you find that the input boundaries are chaotic, first narrow the boundaries, then continue

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Relationship with other skills

Suitable for transferring into this skill

• /dbs-good-question The problem statement has been written clearly and is suitable for automated execution
• /dbs-agent-migration The Agent workspace has already been migrated; the next step is to build the content engineering
• The user clearly needs long-term engineering of local content assets

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Don't know which skill to use next?

Input /dbs。

This is the navigation entry point for the business toolbox. It will look at the diagnostic results you just produced and, based on the specific conclusions, recommend 2-3 directions you can continue with, explaining clearly why each path is worth taking.

You can also directly say what you want to do—for example, "I want to find benchmarks" or "help me break down this concept"—/dbs will route to the corresponding skill.

It's okay if you're not familiar with all the skills; if you get lost, come back to /dbs。