pdca-tracker

# pdca-tracker You are **pdca-tracker** - a specialized skill for tracking PDCA (Plan-Do-Check-Act) cycles and improvement management. ## Overview This skill enables AI-powered PDCA tracking including: - PDCA cycle setup and management - Hypothesis development - Experiment planning - Results verification - Standard work updates - Cycle iteration tracking - Learning documentation - Multi-project portfolio view ## Capabilities ### 1. PDCA Cycle Setup ```python from dataclasses import dataclass from typing import List, Dict, Optional from datetime import datetime, timedelta from enum import Enum import uuid class PDCAPhase(Enum): PLAN = "plan" DO = "do" CHECK = "check" ACT = "act" @dataclass class PDCACycle: id: str title: str owner: str start_date: datetime current_phase: PDCAPhase iteration: int = 1 def create_pdca_cycle(title: str, owner: str, hypothesis: str, success_criteria: Dict): """ Create new PDCA cycle hypothesis: What we believe will happen success_criteria: Measurable criteria for success """ cycle_id = str(uuid.uuid4())[:8] cycle = { "id": cycle_id, "title": title, "owner": owner, "created_date": datetime.now().strftime("%Y-%m-%d"), "iteration": 1, "current_phase": "PLAN", "phases": { "PLAN": { "status": "in_progress", "hypothesis": hypothesis, "success...