Development Pipeline

Organization

ww-w-ai

development-pipeline

Complete 9-phase development pipeline guide — from schema to deployment. Pipeline phases (1-schema → 9-deployment) are orthogonal to PDCA's 9-phase per-feature cycle and Sprint's 8-phase container; each pipeline phase may host PDCA cycles for individual features, and multi-feature pipeline initiatives can be wrapped in /sprint (v2.1.13). Triggers: development pipeline, where to start, phase

Overview

Publisher	ww-w-ai
Repository	`bkit-claude-code`
Skill name	`development-pipeline`
Stars	601
Forks	154
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ww-w-ai on GitHub. Read the source before you install it.

Installation

Install the Development Pipeline AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ww-w-ai/bkit-claude-code.git /tmp/bkit-claude-code
mkdir -p .claude/skills
cp -r /tmp/bkit-claude-code/skills/development-pipeline .claude/skills/development-pipeline

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Development Pipeline in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Development Pipeline on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Development Pipeline is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Development Pipeline Skill

Complete knowledge of the 9-phase development pipeline

When to Use

When user says "I have little development experience"
When using /pipeline-* commands
When asked "How do I start development?", "What's the order?"
When starting a new project from scratch

Optional Application Principle


This skill is optional, not mandatory.

Activation conditions:
- When non-developers/beginner developers start development
- When user explicitly requests guidance
- When /pipeline-start command is used

Deactivation conditions:
- When experienced developers want to "proceed freely"
- For non-development AI work (documentation, analysis, etc.)
- For existing project maintenance/bug fixes

9-Phase Pipeline Overview


Phase 1: Schema/Terminology ──→ Define data structures and domain terms
Phase 2: Coding Convention ────→ Define code writing rules
Phase 3: Mockup Development ───→ Feature validation with HTML/CSS/JS + JSON
Phase 4: API Design/Impl ──────→ Backend API + Zero Script QA
Phase 5: Design System ────────→ Build component system
Phase 6: UI Implementation ────→ Actual UI implementation and API integration
Phase 7: SEO/Security ─────────→ Search optimization and security hardening
Phase 8: Review ───────────────→ Architecture/convention quality verification
Phase 9: Deployment ───────────→ Production deployment

Relationship with PDCA (Key Concept)


❌ Wrong understanding: Mapping entire Pipeline to PDCA
❌ (Plan=Phase1-3, Do=Phase4-6, Check=Phase7-8, Act=Phase9)

✅ Correct understanding: Run PDCA cycle within each Phase

Phase N
├── Plan: Plan what to do in this Phase
├── Design: Detailed design
├── Do: Execute/implement
├── Check: Verify/review
└── Act: Confirm and move to next Phase

Phase Application by Level

Phase	Starter	Dynamic	Enterprise
1. Schema/Terms	Simple	Detailed	Detailed
2. Convention	Basic	Extended	Extended
3. Mockup	O	O	O
4. API	-	bkend.ai	Direct impl
5. Design System	Optional	O	O
6. UI + API	Static UI	Integration	Integration
7. SEO/Security	SEO only	O	O
8. Review	-	O	O
9. Deployment	Static hosting	Vercel etc.	K8s

Starter Level Flow


Phase 1 → 2 → 3 → 5(optional) → 6(static) → 7(SEO) → 9

Dynamic Level Flow


Phase 1 → 2 → 3 → 4(bkend.ai) → 5 → 6 → 7 → 8 → 9

Enterprise Level Flow


Phase 1 → 2 → 3 → 4(direct impl) → 5 → 6 → 7 → 8 → 9

Phase Deliverables Summary

Phase	Key Deliverables
1	`docs/01-plan/schema.md`, `terminology.md`
2	`CONVENTIONS.md`, `docs/01-plan/naming.md`
3	`mockup/` folder, `docs/02-design/mockup-spec.md`
4	`docs/02-design/api-spec.md`, `src/api/`
5	`components/ui/`, `docs/02-design/design-system.md`
6	`src/pages/`, `src/features/`
7	`docs/02-design/seo-spec.md`, `security-spec.md`
8	`docs/03-analysis/architecture-review.md`
9	`docs/04-report/deployment-report.md`

Related Skills

phase-1-schema/ ~ phase-9-deployment/: Detailed guides per Phase
pdca-methodology/: How to apply PDCA
starter/, dynamic/, enterprise/: Level-specific knowledge

Frequently asked questions

What does the Development Pipeline AI skill do?

Why use Development Pipeline on TypingMind?

Because you install it once and use it with any model. Development Pipeline is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Development Pipeline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ww-w-ai/bkit-claude-code/tree/main/skills/development-pipeline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Development Pipeline?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Development Pipeline?

As many as you like. As long as a model supports skills, you can use Development Pipeline with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Development Pipeline AI skill free?

Yes. It is published on GitHub by ww-w-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Development Pipeline Skill

When to Use

Optional Application Principle

9-Phase Pipeline Overview

Relationship with PDCA (Key Concept)

Phase Application by Level

Starter Level Flow

Dynamic Level Flow

Enterprise Level Flow

Phase Deliverables Summary

Related Skills

Frequently asked questions

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