Pdca Batch logo

Pdca Batch

Organization
ww-w-ai
pdca-batch

Manage multiple PDCA features as independent parallel cycles (no shared scope/budget). For multiple features that share scope, budget, or timeline as one cohesive initiative, use /sprint (v2.1.13) — sprint groups features into a single 8-phase container, while pdca-batch keeps them independent. Triggers: pdca-batch, batch, multiple features

Overview

Publisherww-w-ai
Repositorybkit-claude-code
Skill namepdca-batch
Stars
601
Forks
154
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 Batch 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-claude-code.git /tmp/bkit-claude-code
mkdir -p .claude/skills
cp -r /tmp/bkit-claude-code/skills/pdca-batch .claude/skills/pdca-batch
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pdca Batch 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 Batch 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 Batch 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 Batch Skill

User-invocable skill for managing multiple PDCA features and batch operations.

Arguments

ArgumentDescriptionExample
(none)Show all active features (same as status)/pdca-batch
statusShow all active features and their PDCA status/pdca-batch status
plan <f1> <f2> ...Plan multiple features in sequence/pdca-batch plan auth search api
manageInteractive dashboard for parallel features/pdca-batch manage

Action Details

status (Default)

Show all active PDCA features and their current status.

  1. Read .bkit/state/pdca-status.json
  2. Filter to active features (exclude archived/completed unless --all flag)
  3. For each feature, display: phase, matchRate, iterationCount, last updated
  4. Show summary: total active, total completed, total archived
  5. Warn if approaching max parallel limit (3)

Output Format:

--- PDCA Feature Dashboard ------------------------
Active Features: 2/3 (max)

  #  Feature            Phase     Match%  Iter  Last Updated
  1  user-auth          check     85%     2/5   10 min ago
  2  search-api         design    -       0/5   2 hours ago
  -  (1 slot available)

Completed (recent):
  3  payment-flow       archived  96%     3/5   2 days ago

---------------------------------------------------
Totals: 2 active | 1 completed | 0 stale
Tip: Use /pdca-batch manage for interactive control

plan ...

Plan multiple features in a batch sequence.

  1. Parse feature names from arguments (space-separated)
  2. Validate: max 5 features per batch plan
  3. Check current active feature count (max 3 concurrent)
  4. For features exceeding the parallel limit, queue them
  5. Display batch plan summary and ask for confirmation via AskUserQuestion
  6. On confirmation, for each feature sequentially: a. Initialize feature in pdca-status.json (state: idle) b. Create Plan document using plan template c. Record batch origin: batchId in feature metadata
  7. Display batch plan results

Batch Plan Output:

--- Batch Plan Results ----------------------------
Batch ID: batch-1710842700000
Features planned: 3

  Feature       Status    Plan Document
  auth          OK        docs/01-plan/features/auth.plan.md
  search        OK        docs/01-plan/features/search.plan.md
  api-v2        QUEUED    (waiting for slot, 2/3 active)

---------------------------------------------------
Next: Run /pdca design <feature> for each planned feature

Constraints:

  • Maximum 5 features per batch plan command
  • Maximum 3 features active simultaneously
  • Features beyond the limit are queued with phase: queued
  • Queued features auto-activate when a slot becomes available

manage

Interactive dashboard for managing parallel features.

  1. Read all active features from pdca-status.json
  2. Display interactive-style management panel
  3. Show available actions per feature
  4. Accept user input for next action via AskUserQuestion

Output Format:

--- Feature Management Dashboard ------------------
Active Features: 2/3

[1] user-auth (check, 85%, iter 2/5)
    Actions: [a]nalyze  [i]terate  [r]eport  [p]ause

[2] search-api (design, -, iter 0/5)
    Actions: [d]esign-review  [n]ext  [p]ause

[Q] user-input (queued, waiting for slot)
    Actions: [c]ancel  [p]rioritize

---------------------------------------------------
Global Actions:
  [s] Switch active feature
  [n] New feature (if slot available)
  [r] Refresh dashboard
  [x] Exit dashboard
---------------------------------------------------
Select feature number or action:

Management Actions:

ActionDescription
Switch featureChange which feature is "focused" for subsequent /pdca commands
Prioritize queuedMove a queued feature to next available slot
Pause featureTemporarily halt a feature's PDCA progression
Cancel queuedRemove a feature from the queue
New featureStart a new PDCA cycle if slot available

Parallel Feature Rules

  1. Maximum 3 concurrent features: Prevents context overload and resource contention
  2. Independent state: Each feature has its own phase, matchRate, and iteration count
  3. Shared guardrails: Automation level and trust score are global (not per-feature)
  4. Queue system: Features beyond limit are queued and auto-activated on slot availability
  5. Isolation: Features do NOT share checkpoints or audit entries

State File Schema

Features in pdca-status.json with batch support:

json
{
  "user-auth": {
    "phase": "check",
    "matchRate": 85,
    "iterationCount": 2,
    "batchId": "batch-1710842700000",
    "queuePosition": null,
    "lastUpdated": "2026-03-19T10:30:00.000Z"
  },
  "search-api": {
    "phase": "design",
    "matchRate": 0,
    "iterationCount": 0,
    "batchId": "batch-1710842700000",
    "queuePosition": null,
    "lastUpdated": "2026-03-19T08:30:00.000Z"
  },
  "api-v2": {
    "phase": "queued",
    "batchId": "batch-1710842700000",
    "queuePosition": 1,
    "lastUpdated": "2026-03-19T10:30:00.000Z"
  }
}

Module Dependencies

ModuleFunctionUsage
lib/pdca/status.jsgetPdcaStatus()Read all feature states
lib/pdca/status.jsupdatePdcaStatus()Update feature state
lib/pdca/state-machine.jscreateContext()Initialize new feature
lib/pdca/lifecycle.jsactivateQueuedFeature()Auto-activate from queue
lib/audit/audit-logger.jswriteAuditLog()Record batch operations

Usage Examples

bash
# View all features
/pdca-batch

# Plan multiple features
/pdca-batch plan user-auth search-api payment-flow

# Interactive management
/pdca-batch manage

Integration with /pdca

The /pdca-batch skill complements the main /pdca skill:

ScopeUse /pdcaUse /pdca-batch
Single feature operationsYesNo
Multi-feature overviewNoYes
Phase transitionsYesNo (redirects to /pdca)
Batch planningNoYes
Feature switchingNoYes (manage)

When using /pdca commands, they operate on the currently "focused" feature. Use /pdca-batch manage to switch the focused feature.

Frequently asked questions

What does the Pdca Batch AI skill do?

Manage multiple PDCA features as independent parallel cycles (no shared scope/budget). For multiple features that share scope, budget, or timeline as one cohesive initiative, use /sprint (v2.1.13) — sprint groups features into a single 8-phase container, while pdca-batch keeps them independent. Triggers: pdca-batch, batch, multiple features

Why use Pdca Batch on TypingMind?

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

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

Which AI models can use Pdca Batch?

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 Batch?

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

Is the Pdca Batch 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 👇