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cm-dockit

Knowledge systematization engine — analyze codebases, generate Personas, JTBD, Process Flows, technical docs, SOP user guides, API references. Output as Markdown or VitePress Premium. SEO-optimized, AI/LLM-readable. One scan = complete knowledge base.

Install / Use

npx skills add tody-agent/codymaster --skill cm-dockit

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

70/100

Supported Platforms

Zed

Our assessment of cm-dockit

cm-dockit scores 70/100 on our quality scale, 891st of 963 AI & Machine Learning skills we index.

Its SKILL.md is 12 KB long, well organised into 21 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

It has no GitHub stars yet, so there is no community track record; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
0/20
Freshness
5/15

Maintenance, license and trust

  • We could not determine when the repository was last updated.
  • Our last check on 2026-10-20 found the source still online.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

cm-dockit compared with similar skills

All 4 of these similar skills score higher than cm-dockit; compare them before choosing.

SkillScoreStarsUpdatedFormat
cm-dockit (this skill)by tody-agent700—SKILL.md
claude-memby thedotmack100113.6ktodayCLAUDE.md
Agent-Reachby Panniantong100109.3ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10091.0k11d agoCLAUDE.md
headroomby headroomlabs-ai10079.0ktodayCLAUDE.md

Frequently asked questions

How do I install cm-dockit?
Run npx skills add tody-agent/codymaster --skill cm-dockit. The install tabs above show the steps for each supported agent.
Which AI agents does cm-dockit work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is cm-dockit safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is cm-dockit still maintained?
We could not determine when the repository was last updated.

name: cm-dockit description: "Knowledge systematization engine — analyze codebases, generate Personas, JTBD, Process Flows, technical docs, SOP user guides, API references. Output as Markdown or VitePress Premium. SEO-optimized, AI/LLM-readable. One scan = complete knowledge base."

CM DocKit: Knowledge Systematization Engine

A professional knowledge systematization engine powered by codebase analysis and UX design principles. One source scan = one complete knowledge base — Personas, JTBD, Process Flows, Technical Docs, SOPs, API Reference. Supports plain Markdown output or a premium VitePress site. Includes SEO optimization, sitemap generation, and AI/LLM-readable content.

When to Activate

  • User asks to "create documentation", "generate docs"
  • User mentions "SOP", "user guide", "manual"
  • User wants technical docs from a codebase
  • User runs /DocKit Master

Document Types

| Type | Skill File | Description | |------|-----------|-------------| | knowledge | skills/persona-builder.md + skills/jtbd-analyzer.md + skills/flow-mapper.md (files pending) | Personas, JTBD, Process Flows — knowledge foundation | | tech | skills/tech-docs.md | Architecture, database, deployment, data flow | | sop | skills/sop-guide.md | Step-by-step user guides (enriched with knowledge) | | api | skills/api-reference.md | API endpoint reference with examples | | all | All above | Full knowledge base + documentation suite |

| Support Skill | File | Purpose | |--------------|------|---------| | SEO Checklist | skills/seo-checklist.md | Per-page SEO audit (title, meta, headings, robots) | | Content Writing | skills/content-writing.md | SEO copywriting, keywords, active voice, FAQ | | LLM Optimization | skills/llm-optimization.md | AI-readable structure, NotebookLM-friendly |

Output Formats

| Format | Workflow | Description | |--------|---------|-------------| | markdown | workflows/export-markdown.md | Plain .md files in docs/ folder | | vitepress | workflows/setup-vitepress.md | Premium VitePress static site (default) — built-in Mermaid, search, dark mode |

Procedure

Step 1: Gather Input (Single Consolidated Prompt)

CRITICAL: Ask ALL questions in ONE message. Do NOT ask one at a time. Present the following intake form to the user, using this 📚 DocKit Master — Configuration

Please answer the following questions so I can automatically create an execution plan:

| # | Question | Options | Default | |---|---------|---------|--------| | 1 | 📑 Document type? | knowledge · tech · sop · api · all | all | | 2 | 🎨 Output format? | markdown (plain) · vitepress (premium site) | vitepress | | 3 | 📂 Code scan scope? | full (entire project) · focused (specific folder/feature) | full | | 4 | 🎯 Focus area? (only if focused) | Folder name, module, or specific feature | — | | 5 | 🌏 Writing language? | Auto-detect from chat language (see below) | auto-detect | | 6 | 🌐 Add multi-language? | yes (add English + source language) · no | no | | 7 | 📹 Record video demo? | yes (record browser walkthrough) · no | no | | 8 | 📁 Project path? | (absolute path) | current workspace | | 9 | 🔍 SEO optimization? | yes (SEO frontmatter + checklist + sitemap) · no | yes | | 10 | 🤖 Optimize for AI/LLM? | yes (AI-readable + NotebookLM sitemap) · no | yes |

You can answer briefly, e.g.: "all, vitepress, full, yes, no, yes, yes"

🌏 Smart language rules:

  1. Auto-detect: Determine default language from the user's chat language
    • User chats in Vietnamese → default vi
    • User chats in Chinese → default zh
    • User chats in Japanese → default ja
    • User chats in English → default en
    • (Applies similarly for any other language)
  2. Multi-language (yes): Automatically add English (en) as secondary language
    • Example: Vietnamese user + multi-language → vi + en
    • Example: Chinese user + multi-language → zh + en
    • If user already chats in English + multi-language → ask which secondary language
  3. Override: User can override by specifying explicitly, e.g.: "write in Japanese"

Step 1b: Auto-Generate Execution Plan

After receiving answers, immediately create an execution plan (do NOT ask more questions).

Map the answers to this execution config:

DOC_TYPE     = [knowledge | tech | sop | api | all]
FORMAT       = [markdown | vitepress]
SCOPE        = [full | focused]
FOCUS_TARGET = [directory/module name if focused, else null]
LANGUAGE     = [vi | en | vi+en]
I18N         = [yes | no] (only relevant for vitepress)
RECORD       = [yes | no]
PROJECT_PATH = [absolute path]
SEO          = [yes | no] (default: yes)
LLM_OPTIMIZE = [yes | no] (default: yes)

Then present the plan to user as a checklist artifact, like:

## 🚀 Execution Plan

- [ ] Scan code: [full/focused → target]
- [ ] Generate documents: [type] in [language]
- [ ] Export format: [markdown/vitepress]
- [ ] [If vitepress + i18n] Configure multi-language
- [ ] [If record] Record video walkthrough
- [ ] [If seo] Run SEO checklist + generate sitemap
- [ ] [If llm_optimize] Apply LLM optimization rules
- [ ] Review and deliver

After presenting the plan → proceed to Step 2 immediately (auto-execute). Do NOT wait for approval unless the plan has ambiguity.

Step 2: Analyze Codebase

Read and follow skills/analyze-codebase.md in this directory.

Output: structured analysis saved to docs/analysis.md (NOT _analysis.md) including:

  • Project type, languages, frameworks
  • Directory structure and architecture layers
  • Entry points, routes, database schema
  • Key business logic modules
  • Dependencies overview
  • Test coverage

Step 3: Apply Content Guidelines

MANDATORY — Read skills/content-guidelines.md before generating any content.

Key rules to enforce:

  • Filenames: kebab-case, no underscores, no dots
  • Frontmatter: Every .md file must have title, description, keywords, robots
  • Quick Reference: Every doc starts with a summary box
  • Progressive Disclosure: Use <details> for advanced content
  • Admonitions: Use :::tip, :::info, :::warning, :::danger for callouts
  • Mermaid: NO hardcoded colors — VitePress auto-adapts to light/dark
  • Code Groups: Use :::code-group for multi-platform examples
  • Internal Links: ≥2 cross-links per page

Step 3b: Apply SEO & LLM Guidelines (If enabled)

If SEO = yes: Read skills/content-writing.md for:

  • Keyword placement (title, H1, first paragraph, H2s, meta)
  • Inverted pyramid structure (answer first, details later)
  • Active voice (≥80%), transition words (≥30%)
  • FAQ in schema-ready format for rich snippets

If LLM_OPTIMIZE = yes: Read skills/llm-optimization.md for:

  • Clean heading hierarchy (no skipped levels)
  • Text descriptions alongside all Mermaid diagrams
  • Self-contained sections (≤500 words per H2)
  • Consistent terminology (glossary section in index)
  • UTF-8 clean output

Step 4: Generate Documents

Based on the chosen type, read and follow the corresponding skill file:

  • knowledge → Run 3 skills sequentially:

    1. Read skills/persona-builder.md → docs/personas/ (Buyer & User Personas)
    2. Read skills/jtbd-analyzer.md → docs/jtbd/ (JTBD Canvases)
    3. Read skills/flow-mapper.md → docs/flows/ (Workflow, Sequence, Lifecycle, Journey)
  • tech → Read skills/tech-docs.md, generate:

    • docs/architecture.md — System architecture + ADR
    • docs/database.md — Database schema & data model
    • docs/deployment.md — Deployment & infrastructure
    • docs/data-flow.md — Data flow diagrams
  • sop → Auto-run knowledge first if not yet generated, then:

    • Read skills/sop-guide.md, generate:
    • docs/sop/ — One .md per feature/module
    • Each file: Persona Context → Process Flow → Steps → Journey → Troubleshooting → FAQ
  • api → Read skills/api-reference.md, generate:

    • docs/api/ — Organized by resource
    • Each file: Quick Ref → Endpoints table → Multi-language examples
  • all → Run knowledge → tech → sop → api sequentially

Step 5: Export

Based on the chosen format, read and follow the corresponding workflow:

  • markdown → Read workflows/export-markdown.md

    • Create docs/README.md as index
    • Organize into clean folder structure
  • vitepress → Read workflows/setup-vitepress.md

    • Scaffold VitePress with premium template
    • Auto-sidebar from folder structure
    • Built-in Mermaid, search, dark mode
    • Build and verify

Step 5b: Generate Sitemap (If SEO = yes)

Read and follow workflows/generate-sitemap.md:

  • VitePress: Sitemap auto-generated via sitemap config option. Generate robots.txt, extract sitemap-urls.txt
  • Markdown: Generate docs/sitemap.md (link index) + docs/sitemap-urls.txt
  • Both formats produce a NotebookLM-ready URL list for AI research

Step 5c: Run SEO Audit (If SEO = yes)

Read skills/seo-checklist.md and audit every generated page:

  • Title (50–60 chars, keyword) ✔️
  • Meta description (150–160 chars) ✔️
  • Single H1, no skipped levels ✔️
  • ≥2 internal links ✔️
  • Robots directive set ✔️
  • All images have alt text ✔️

Step 6: Summary

Present to user:

  • List of generated files with sizes
  • How to view/serve the docs
  • Next steps (customize, deploy, etc.)

If generated docs > 30 files, also suggest:

💡 **Pro Tip: Deep Search**

The documentation set just created has [X] files. You can index them using
[qmd](https://github.com/tobi/qmd) for semantic search by AI
across all future sessions:

\`\`\`bash
npm install -g @tobilu/qmd
qmd collection add ./docs --name project-docs
qmd context add qmd://project-docs "Project documentation for [project-name]"
qmd embed
\`\`\`

See also: `cm-deep-search` skill.

CLI Quick Start

For a fast interactive experience, users can run the doc generation script from the skill root:

# Run from the cm-dockit skill directory
bash scripts/doc-gen.sh

Note: The scripts/ directory and doc-gen.sh script need to be created. For now, trigger this skill by invoking cm-dockit directly via the AI assistant.

UX Principles Applied

| UX Law | Application | |--------|-------------| | Hick's Law | ≤7 TOC items, progressive disclosure for advanced content | | Miller's Law | Information chunked into groups of 5-9 | | Doherty Threshold | Tables for structured data, scannable summaries | | Jakob's Law | Standard doc layout (sidebar + content + TOC) | | Fitts's Law | Touch-friendly navbar links (≥44px) | | WCAG 2.1 AA | Focus-visible rings, high contrast, reduced motion |

Constraints

  • All Mermaid diagrams use NO hardcoded inline styles — VitePress theming handles light/dark
  • Every technical claim cites (file_path:line_number)
  • SOP docs use <details> for troubleshooting (progressive disclosure)
  • All generated files include YAML frontmatter with title, description
  • Pure Markdown — no MDX, no special escaping needed
  • No underscore-prefixed filenames — breaks auto-sidebar detection
  • VitePress output must pass npx vitepress build without errors
  • SEO default: robots: "index, follow" unless page is internal/draft
  • ≥2 internal links per page (never orphan pages)
  • Text fallback for every Mermaid diagram (LLM readability)
  • Self-contained sections — each H2 makes sense read alone
  • sitemap-urls.txt generated for NotebookLM import

CM DocKit Development Rules

If you are an AI agent asked to modify or upgrade this skill (CM DocKit):

  1. Test Gate Enforcement: You MUST run the backend test suite located in the cm-dockit skill directory by executing $ npm run test:gate or $ vitest. Do NOT claim "task completed" unless tests pass.
  2. Boilerplate Integrity: If modifying `temp

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars0
CategoryAI
UpdatedNaNy ago
Forks0

Trust signals

68/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

2 medium1 low