Pdca logo

Pdca

Organization
ww-w-ai
pdca

Unified skill for managing the entire PDCA cycle. Supports Plan → Design → Do → Check → Act workflow with automatic phase progression. Use proactively when user mentions PDCA cycle, planning, design documents, gap analysis, iteration, or completion reports. Triggers: pdca, plan, design, analyze, check, report, status, next, iterate, 계획, 설계, 분석, 검증, 보고서, 반복, 개선, 計画, 設計, 分析, 検証, 報告, 反復, 计划, 设计, 分析, 验证, 报告, 迭代, planificar, diseño, analizar, verificar, informe, planifier, conception, analyser, vérifier, rapport, planen, Entwurf, analysieren, überprüfen, Bericht, pianificare, progettazione, analizzare, verificare, rapporto Do NOT use for: simple one-line fixes, non-development tasks

Overview

Publisherww-w-ai
Repositorybkit-gemini
Skill namepdca
Stars
66
Forks
16
Bundled files
Instructions only
LicenseApache-2.0
Links
  • 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 Pdca AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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-gemini.git /tmp/bkit-gemini
mkdir -p .claude/skills
cp -r /tmp/bkit-gemini/skills/pdca .claude/skills/pdca
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pdca 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 Pdca 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 Pdca 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.

PDCA Skill

Unified Skill for managing PDCA cycle. Supports the entire Plan → Design → Do → Check → Act flow.

Arguments

ArgumentDescriptionExample
plan [feature]Create Plan document/pdca plan user-auth
design [feature]Create Design document/pdca design user-auth
do [feature]Do phase guide/pdca do user-auth
analyze [feature]Run Gap analysis (Check)/pdca analyze user-auth
iterate [feature]Auto improvement (Act)/pdca iterate user-auth
report [feature]Generate completion report/pdca report user-auth
archive [feature]Archive PDCA documents/pdca archive user-auth
statusShow current status/pdca status
nextGuide to next phase/pdca next

Action Details

plan (Plan Phase)

  1. Check if docs/01-plan/features/{feature}.plan.md exists

  2. If not, create based on plan.template.md

  3. Create Task: [Plan] {feature}

  4. Context Anchor Generation: After generating Plan document, extract Context Anchor (WHY/WHO/RISK/SUCCESS/SCOPE) from Executive Summary, Requirements, and Risk sections. Write as ## Context Anchor table between Executive Summary and Section 1.

    DimensionContent
    WHYCore problem being solved
    WHOTarget users/stakeholders
    RISKTop 3 risks identified
    SUCCESSMeasurable success criteria
    SCOPEIn-scope / out-of-scope boundary

design (Design Phase)

  1. Verify Plan document exists
  2. Create docs/02-design/features/{feature}.design.md
  3. Create Task: [Design] {feature} (blockedBy: Plan)
  4. Context Anchor Embed: Copy Plan's ## Context Anchor table to Design document top (between header metadata and ## 1. Overview). If Plan has no Context Anchor, skip gracefully.
  5. Generate 3 Architecture Options:
    • Option A — Minimal Changes: Least modification, maximum reuse
    • Option B — Clean Architecture: Best separation of concerns
    • Option C — Pragmatic Balance: Good boundaries without over-engineering
  6. Present comparison table with trade-offs (complexity, maintainability, effort, risk)
  7. Ask user which option to select before proceeding

do (Do Phase)

  1. Verify Design document exists
  2. Provide implementation guide
  3. Create Task: [Do] {feature} (blockedBy: Design)
  4. Full Upstream Context Loading: Read ALL upstream documents:
    • PRD (docs/00-pm/{feature}.prd.md) — WHY context
    • Plan (docs/01-plan/features/{feature}.plan.md) — Context Anchor, Success Criteria
    • Design document — architecture decisions
  5. Decision Record Chain Display:
    Decision Record Chain
    [PRD] Target: {segment} — {rationale}
    [Plan] Architecture: {option} — {rationale}
    [Design] Pattern: {approach} — {rationale}
  6. Display Context Anchor from Design document header
  7. Parse --scope parameter: If --scope module-1 provided, filter implementation guide to matching modules only from Design's Session Guide
  8. Ask user to confirm scope before starting implementation

analyze (Check Phase)

  1. Call gap-detector agent
  2. Compare Design vs implementation
  3. Calculate Match Rate
  4. Create Task: [Check] {feature}
  5. After gap-detector analysis, also call bkit_iterate MCP tool for quantitative gap measurement:
    • This tool compares design document vs actual implementation
    • Returns matchRate percentage and specific gaps with file references
    • If matchRate < 90%, recommend calling /pdca iterate

iterate (Act Phase)

  1. Check results (when matchRate < 90%)
  2. Call pdca-iterator agent
  3. Auto-fix and re-verify
  4. Max 5 iterations
  5. Call bkit_iterate MCP tool for automated gap analysis:
    • Input: feature name, project directory, target match rate (default 90%)
    • Tool returns gaps with specific file:line references
    • Fix the identified gaps
    • Call bkit_iterate again to re-check
    • Repeat until matchRate >= 90% or max 5 iterations
    • Server tracks iteration count internally

qa (QA Phase)

When running QA, call bkit_qa_run MCP tool:

  • Input: feature name, project directory, test levels [1,2,3,4,5]
  • The tool auto-detects test framework (jest/vitest/playwright)
  • L1: Unit tests, L2: API tests, L3-L5: E2E/browser tests (if playwright installed)
  • Review results: passRate, coverage, defects
  • If passRate < 95%, fix issues and re-run

report (Completion Report)

  1. Verify Check >= 90%
  2. Call report-generator agent
  3. Create completion report
  4. Load ALL upstream documents for comprehensive reporting:
    • PRD — compare original value proposition vs delivered value
    • Plan — compare planned Success Criteria vs actual results
    • Design — note architecture decisions and any deviations
    • Analysis — include final Match Rate
  5. Include Decision Record summary and Success Criteria final status

PDCA Flow

[Plan] ✅ → [Design] ✅ → [Do] ✅ → [Check] 🔄 → [Act] ⏳ → [Report] 📋
                                       ↑_________|
                                    (if < 90%)

References

  • ${extensionPath}/templates/plan.template.md
  • ${extensionPath}/templates/design.template.md
  • ${extensionPath}/templates/analysis.template.md
  • ${extensionPath}/templates/report.template.md

Frequently asked questions

What does the Pdca AI skill do?

Unified skill for managing the entire PDCA cycle. Supports Plan → Design → Do → Check → Act workflow with automatic phase progression. Use proactively when user mentions PDCA cycle, planning, design documents, gap analysis, iteration, or completion reports. Triggers: pdca, plan, design, analyze, check, report, status, next, iterate, 계획, 설계, 분석, 검증, 보고서, 반복, 개선, 計画, 設計, 分析, 検証, 報告, 反復, 计划, 设计, 分析, 验证, 报告, 迭代, planificar, diseño, analizar, verificar, informe, planifier, conception, analyser, vérifier, rapport, planen, Entwurf, analysieren, überprüfen, Bericht, pianificare, progettazione, anal...

Why use Pdca on TypingMind?

Because you install it once and use it with any model. Pdca 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 Pdca in TypingMind?

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

Which AI models can use Pdca?

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 Pdca?

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

Is the Pdca 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇