kanban

name	kanban
version	1.0.0
description	[Project Management] Use when you need aI agent orchestration board (Coming Soon).
disable-model-invocation	false

Quick Summary

Goal: Launch a visual plans dashboard with progress tracking, phase status, and timeline visualization.

Workflow:

1. Invoke — /kanban or /kanban plans/ to view, /kanban --stop to stop
2. Start Server — Run server.cjs as background task with run_in_background: true
3. Report URL — Parse JSON output and display full URL (including query string) to user

Key Rules:

• Always run server as Claude Code background task (visible in /tasks)
• Never truncate URL to just host:port; display full path + query string
• Set timeout: 300000 to prevent premature termination

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Plans dashboard with progress tracking and timeline visualization.

Usage

• /kanban - View dashboard for ./plans directory
• /kanban plans/ - View dashboard for specific directory
• /kanban --stop - Stop running server

Features

• Plan cards with progress bars
• Phase status breakdown (completed, in-progress, pending)
• Timeline/Gantt visualization
• Activity heatmap
• Issue and branch links

Execution

IMPORTANT: Run server as Claude Code background task using run_in_background: true with the Bash tool. This makes the server visible in /tasks and manageable via KillShell.

Check if this script is located in the current workspace or in $HOME/.claude/skills/plans-kanban directory:

• If in current workspace: $SKILL_DIR_PATH = ./.claude/skills/plans-kanban/
• If in home directory: $SKILL_DIR_PATH = $HOME/.claude/skills/plans-kanban/

Stop Server

If --stop flag is provided:

node $SKILL_DIR_PATH/scripts/server.cjs --stop

Start Server

Otherwise, run the kanban server as CC background task with --foreground flag (keeps process alive for CC task management):

# Determine plans directory
INPUT_DIR="{{dir}}"
PLANS_DIR="${INPUT_DIR:-./plans}"

# Start kanban dashboard (loopback-only by design)
node $SKILL_DIR_PATH/scripts/server.cjs \
  --dir "$PLANS_DIR" \
  --host localhost \
  --open \
  --foreground

Critical: When calling the Bash tool:

• Set run_in_background: true to run as CC background task
• Set timeout: 300000 (5 minutes) to prevent premature termination
• Parse JSON output and report URL to user

Example Bash tool call:

{
    "command": "node .claude/skills/plans-kanban/scripts/server.cjs --dir \"./plans\" --host localhost --open --foreground",
    "run_in_background": true,
    "timeout": 300000,
    "description": "Start kanban server in background"
}

After starting, parse the JSON output (e.g., {"success":true,"url":"http://localhost:3500/kanban?dir=..."}) and report:

• Local URL for browser access
• Inform user that server is now running as CC background task (visible in /tasks)

CRITICAL: MUST ATTENTION display the FULL URL including path and query string. NEVER truncate to just host:port. The full URL is required for direct access.

Future Plans

The /kanban command will evolve into VibeKanban-inspired AI agent orchestration:

Phase 1 (Current - MVP)

• ✅ Task board with progress tracking
• ✅ Visual representation of plans/tasks
• ✅ Click to view plan details

Phase 2 (Worktree Integration)

• Create tasks → spawn git worktrees
• Assign agents to tasks
• Track agent progress per worktree

Phase 3 (Full Orchestration)

• Parallel agent execution monitoring
• Code diff/review interface
• PR creation workflow
• Agent output streaming
• Conflict detection

Track progress: https://github.com/claudekit/claudekit-engineer/issues/189

---

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.