visualize-plan

Installation
SKILL.md
Contains Hooks

This skill uses Claude hooks which can execute code automatically in response to events. Review carefully before installing.

Plan Visualization

Render planned changes as structured ASCII visualizations with risk analysis, execution order, and impact metrics. Every section answers a specific reviewer question.

Core principle: Encode judgment into visualization, not decoration.

/ork:visualize-plan                          # Auto-detect from current branch
/ork:visualize-plan billing module redesign  # Describe the plan
/ork:visualize-plan #234                     # Pull from GitHub issue

Argument Resolution

PLAN_INPUT = "$ARGUMENTS"    # Full argument string
PLAN_TOKEN = "$ARGUMENTS[0]" # First token — could be issue "#234" or plan description
# If starts with "#", treat as GitHub issue number. Otherwise, plan description.
# $ARGUMENTS (full string) for multi-word descriptions (CC 2.1.59 indexed access)

CRITICAL: Task Tracking

# 1. Create main task IMMEDIATELY
TaskCreate(subject="Visualize plan: {PLAN_INPUT}", description="Plan visualization with ASCII rendering", activeForm="Analyzing plan context")

# 2. Create subtasks for each phase
TaskCreate(subject="Detect or clarify plan context", activeForm="Detecting plan context")          # id=2
TaskCreate(subject="Gather data and explore architecture", activeForm="Gathering plan data")       # id=3
TaskCreate(subject="Render tier 1 header", activeForm="Rendering header")                          # id=4
TaskCreate(subject="Render requested sections", activeForm="Rendering sections")                   # id=5
TaskCreate(subject="Offer actions and store in memory", activeForm="Finalizing visualization")     # id=6

# 3. Set dependencies for sequential phases
TaskUpdate(taskId="3", addBlockedBy=["2"])  # Data gathering needs context first
TaskUpdate(taskId="4", addBlockedBy=["3"])  # Header needs gathered data
TaskUpdate(taskId="5", addBlockedBy=["4"])  # Sections need header rendered
TaskUpdate(taskId="6", addBlockedBy=["5"])  # Actions need sections done

# 4. Before starting each task, verify it's unblocked
task = TaskGet(taskId="2")  # Verify blockedBy is empty

# 5. Update status as you progress
TaskUpdate(taskId="2", status="in_progress")  # When starting
TaskUpdate(taskId="2", status="completed")    # When done — repeat for each subtask

STEP -1: Check Memory for Prior Plans

# Search for related prior visualizations
mcp__memory__search_nodes(query="plan visualization {PLAN_INPUT}")
# If found, offer to compare with previous plan

STEP 0: Detect or Clarify Plan Context

First, attempt auto-detection by running scripts/detect-plan-context.sh:

bash "$SKILL_DIR/scripts/detect-plan-context.sh"

This outputs branch name, issue number (if any), commit count, and file change summary.

If auto-detection finds a clear plan (branch with commits diverging from main, or issue number in args), proceed to Step 1.

If ambiguous, clarify with AskUserQuestion:

AskUserQuestion(
  questions=[{
    "question": "What should I visualize?",
    "header": "Source",
    "options": [
      {"label": "Current branch changes (Recommended)", "description": "Auto-detect from git diff against main", "markdown": "```\nBranch Diff Analysis\n────────────────────\n$ git diff main...HEAD\n\n→ File change manifest (+A, M, -D)\n→ Execution swimlane by phase\n→ Risk dashboard + pre-mortems\n→ Impact summary (lines, tests, API)\n```"},
      {"label": "Describe the plan", "description": "I'll explain what I'm planning to change", "markdown": "```\nPlan Description\n────────────────\nYou describe → I visualize:\n\n→ Before/after architecture diagrams\n→ Execution order with dependencies\n→ Risk analysis per component\n→ Decision log (ADR-lite format)\n```"},
      {"label": "GitHub issue", "description": "Pull plan from a specific issue number", "markdown": "```\nGitHub Issue Source\n───────────────────\n$ gh issue view #N\n\n→ Extract requirements from body\n→ Map to file-level changes\n→ Generate execution phases\n→ Link back to issue for tracking\n```"},
      {"label": "Quick file diff only", "description": "Just show the change manifest, skip analysis", "markdown": "```\nQuick File Diff\n───────────────\n[A] src/new-file.ts        +120\n[M] src/existing.ts    +15  -8\n[D] src/old-file.ts        -45\n─────────────────────────────\nNET: +82 lines, 3 files\n\nNo risk analysis or swimlanes\n```"}
    ],
    "multiSelect": false
  }]
)

STEP 1: Gather Data

Run scripts/analyze-impact.sh for precise counts:

bash "$SKILL_DIR/scripts/analyze-impact.sh"

This produces: files by action (add/modify/delete), line counts, test files affected, and dependency changes.

For architecture-level understanding, spawn an Explore agent on the affected directories:

Agent(
  subagent_type="Explore",
  prompt="Explore the architecture of {affected_directories}. Return: component diagram, key data flows, health scores per module. Use the ascii-visualizer skill for diagrams.",
  model="haiku"
)

STEP 2: Render Tier 1 Header (Always)

Use assets/tier1-header.md template. Load Read("${CLAUDE_SKILL_DIR}/references/visualization-tiers.md") for field computation (risk level, confidence, reversibility).

PLAN: {plan_name} ({issue_ref})  |  {phase_count} phases  |  {file_count} files  |  +{added} -{removed} lines
Risk: {risk_level}  |  Confidence: {confidence}  |  Reversible until {last_safe_phase}
Branch: {branch} -> {base_branch}

[1] Changes  [2] Execution  [3] Risks  [4] Decisions  [5] Impact  [all]

STEP 3: Ask Which Sections to Expand

AskUserQuestion(
  questions=[{
    "question": "Which sections to render?",
    "header": "Sections",
    "options": [
      {"label": "All sections", "description": "Full visualization with all 5 core sections", "markdown": "```\n[1] Change Manifest   [A]/[M]/[D] file tree\n[2] Execution         Swimlane with phases\n[3] Risks             Dashboard + pre-mortems\n[4] Decisions         ADR-lite decision log\n[5] Impact            Lines, tests, API, deps\n```"},
      {"label": "Changes + Execution", "description": "File diff tree and execution swimlane", "markdown": "```\n[1] Change Manifest\n    [M] src/auth.ts         +45 -12\n    [A] src/oauth.ts        +89\n\n[2] Execution Swimlane\n    Phase 1 ====[auth]========▶\n    Phase 2 ----[blocked]--===▶\n```"},
      {"label": "Risks + Decisions", "description": "Risk dashboard and decision log", "markdown": "```\n[3] Risk Dashboard\n    MEDIUM ██░░ migration reversible\n    HIGH   ███░ API breaking change\n    Pre-mortem: \"What if auth fails?\"\n\n[4] Decision Log\n    D1: OAuth2 over JWT (security)\n    D2: Postgres over Redis (durability)\n```"},
      {"label": "Impact only", "description": "Just the numbers: files, lines, tests, API surface", "markdown": "```\n[5] Impact Summary\n    ┌──────────┬─────┬───────┐\n    │ Metric   │Count│ Delta │\n    ├──────────┼─────┼───────┤\n    │ Files    │  12 │  +3   │\n    │ Lines    │ 450 │ +127  │\n    │ Tests    │   8 │  +4   │\n    │ API sfc  │   3 │  +1   │\n    └──────────┴─────┴───────┘\n```"}
    ],
    "multiSelect": false
  }]
)

STEP 4: Render Requested Sections

Render each requested section following ${CLAUDE_SKILL_DIR}/rules/section-rendering.md conventions. Use the corresponding reference for ASCII patterns:

Section Reference Key Convention
[1] Change Manifest (load ${CLAUDE_SKILL_DIR}/references/change-manifest-patterns.md) [A]/[M]/[D] + +N -N per file
[2] Execution Swimlane (load ${CLAUDE_SKILL_DIR}/references/execution-swimlane-patterns.md) === active, --- blocked, | deps
[3] Risk Dashboard (load ${CLAUDE_SKILL_DIR}/references/risk-dashboard-patterns.md) Reversibility timeline + 3 pre-mortems
[4] Decision Log (load ${CLAUDE_SKILL_DIR}/references/decision-log-patterns.md) ADR-lite: Context/Decision/Alternatives/Tradeoff
[5] Impact Summary (load ${CLAUDE_SKILL_DIR}/assets/impact-dashboard.md) Table: Added/Modified/Deleted/NET + tests/API/deps

STEP 5: Offer Actions

After rendering, offer next steps:

AskUserQuestion(
  questions=[{
    "question": "What next?",
    "header": "Actions",
    "options": [
      {"label": "Write to designs/", "description": "Save as designs/{branch}.md for PR review", "markdown": "```\nSave to File\n────────────\ndesigns/\n  └── feat-billing-redesign.md\n      ├── Header + metadata\n      ├── All rendered sections\n      └── Ready for PR description\n```"},
      {"label": "Generate GitHub issues", "description": "Create issues from execution phases with labels and milestones", "markdown": "```\nGitHub Issues\n─────────────\n#101 [billing] Phase 1: Schema migration\n     labels: component:billing, risk:medium\n#102 [billing] Phase 2: API endpoints\n     labels: component:billing, risk:low\n     blocked-by: #101\n```"},
      {"label": "Drill deeper", "description": "Expand blast radius, cross-layer check, or migration checklist", "markdown": "```\nDeep Dive Options\n─────────────────\n[6] Blast Radius\n    direct → transitive → test impact\n[7] Cross-Layer Consistency\n    Frontend ↔ Backend endpoint gaps\n[8] Migration Checklist\n    Ordered runbook with time estimates\n```"},
      {"label": "Done", "description": "Plan visualization complete"}
    ],
    "multiSelect": false
  }]
)

Write to file: Save full report to designs/{branch-name}.md using assets/plan-report.md template.

Generate issues: For each execution phase, create a GitHub issue with title [{component}] {phase_description}, labels (component + risk:{level}), milestone, body from plan sections, and blocked-by references.

Store in memory: Save plan summary to knowledge graph for future comparison:

mcp__memory__create_entities(entities=[{
  "name": "Plan: {plan_name}",
  "entityType": "plan-visualization",
  "observations": [
    "Branch: {branch}",
    "Risk: {risk_level}, Confidence: {confidence}",
    "Phases: {phase_count}, Files: {file_count}",
    "Key decisions: {decision_summary}"
  ]
}])

Deep Dives (Tier 3, on request)

Available when user selects "Drill deeper". Load Read("${CLAUDE_SKILL_DIR}/references/deep-dives.md") for cross-layer and migration patterns.

Section What It Shows Reference
[6] Blast Radius Concentric rings of impact (direct -> transitive -> tests) (load ${CLAUDE_SKILL_DIR}/references/blast-radius-patterns.md)
[7] Cross-Layer Consistency Frontend/backend endpoint alignment with gap detection (load ${CLAUDE_SKILL_DIR}/references/deep-dives.md)
[8] Migration Checklist Ordered runbook with sequential/parallel blocks and time estimates (load ${CLAUDE_SKILL_DIR}/references/deep-dives.md)

Key Principles

Principle Application
Progressive disclosure Tier 1 header always, sections on request
Judgment over decoration Every section answers a reviewer question
Precise over estimated Use scripts for file/line counts
Honest uncertainty Confidence levels, pre-mortems, tradeoff costs
Actionable output Write to file, generate issues, drill deeper
Anti-slop No generic transitions, no fake precision, no unused sections

Rules Quick Reference

Rule Impact What It Covers
section-rendering (load ${CLAUDE_SKILL_DIR}/rules/section-rendering.md) HIGH Rendering conventions for all 5 core sections
ASCII diagrams MEDIUM Via ascii-visualizer skill (box-drawing, file trees, workflows)

References

Load on demand with Read("${CLAUDE_SKILL_DIR}/references/<file>"):

File Content
visualization-tiers.md Progressive disclosure tiers and header field computation
change-manifest-patterns.md Change manifest ASCII patterns
execution-swimlane-patterns.md Execution swimlane ASCII patterns
risk-dashboard-patterns.md Risk dashboard ASCII patterns
decision-log-patterns.md Decision log ASCII patterns
blast-radius-patterns.md Blast radius ASCII patterns
deep-dives.md Cross-layer consistency and migration checklist

Assets

Load on demand with Read("${CLAUDE_SKILL_DIR}/assets/<file>"):

File Content
plan-report.md Full mustache-style report template
impact-dashboard.md Impact table template
tier1-header.md 5-line summary template

Related Skills

  • ork:implement - Execute planned changes
  • ork:explore - Understand current architecture
  • ork:assess - Evaluate complexity and risks
  • ork:memory - Search prior plan visualizations
  • ork:remember - Store plan decisions for future reference
Weekly Installs
5
GitHub Stars
150
First Seen
Mar 11, 2026
Installed on
antigravity5
opencode4
gemini-cli4
amp4
cline4
github-copilot4