ork-assess
Assess a code change, design, architecture, workflow, or competing options against explicit criteria and evidence. Use when a request asks to assess, rate,…
Renders planned changes — architecture and before/after comparisons, risk heat maps, execution order, dependency graphs, impact metrics — in your chosen output format (ASCII + emojis, an interactive HTML playground, or a NotebookLM infographic). Stores visualizations in memory
$ npx -y skills add yonatangross/orchestkit --skill visualize-plan --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/visualize-planContext preview
The summary Claude sees to decide when to auto-load this skill.
Renders planned changes — architecture and before/after comparisons, risk heat maps, execution order, dependency graphs, impact metrics — in your chosen output format (ASCII + emojis, an interactive HTML playground, or a NotebookLM infographic). Stores visualizations in memory
name: visualize-plan
license: MIT
compatibility: "Claude Code 2.1.251+."
description: "Renders planned changes — architecture and before/after comparisons, risk heat maps, execution order, dependency graphs, impact metrics — in your chosen output format (ASCII + emojis, an interactive HTML playground, or a NotebookLM infographic). Stores visualizations in memory for cross-session reference. Use when reviewing implementation plans, comparing approaches, assessing risk, or analyzing change propagation."
argument-hint: "[plan-or-issue]"
context: fork
# user-typed commands stay interactive; CC >= 2.1.218 backgrounds forks by default (#3093)
background: false
agent: workflow-architect
model: sonnet
version: 2.1.0
author: OrchestKit
tags: [visualization, planning, before-after, architecture, diff, risk, impact, migration, playground, infographic, multi-format]
user-invocable: true
allowed-tools: [Read, Grep, Glob, Agent, TaskCreate, TaskUpdate, AskUserQuestion, Bash, Write, mcp__memory__search_nodes, mcp__memory__create_entities, ToolSearch]
skills: [glyph, explore, architecture-decision-record, memory, remember, page-serve]
complexity: medium
persuasion-type: guidance
hooks:
PreToolUse:
- matcher: "Bash"
command: "${CLAUDE_PLUGIN_ROOT}/hooks/bin/run-hook.mjs skill/plan-context-loader"
once: true
metadata:
category: document-asset-creation
mcp-server: memory
triggers:
keywords: [visualize, "visualize plan", "visualize the plan", "visualize the", "show diagram", "before and after", "execution order", "risk and impact", swimlane, "what files will change"]
examples:
- "visualize the plan for the billing module redesign"
- "show me a before and after diagram for this migration"
- "whats the risk and impact of the changes"
anti-triggers: [implement, brainstorm, explore, assess, fix]Render planned changes as structured ASCII visualizations with risk analysis, execution order, and impact metrics. Every section answers a specific reviewer question.
**Core principle:** Encode judgment into visualization, not decoration.
visualize-plan # Auto-detect from current branch visualize-plan billing module redesign # Describe the plan visualize-plan #234 # Pull from GitHub issue visualize-plan --quick # Header + changes + impact, zero questions visualize-plan --playground # Skip straight to the HTML dashboard visualize-plan --infographic # Skip straight to NotebookLM
PLAN_INPUT = "$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) # Flags are stripped from PLAN_INPUT before it is used as a description: # --quick → QUICK=true: tier-1 header + [1] Changes + [5] Impact, no Explore # agent, no questions at all, no memory write. The 15-second answer. # --playground → FORMATS=[ascii, playground] (no format question) # --infographic → FORMATS=[ascii, infographic] (no format question) # --all → FORMATS=[ascii, + everything the probe found]
This skill used to ask three blocking questions (source, then format, then sections) before a single character rendered, plus a fourth after. That is why fast paths leaked to `glyph` and to hand-written HTML.
The format answer is **not needed** to render ASCII — the ASCII floor rule renders it first regardless of what the user picks. So asking up front buys nothing and costs a round-trip. The rule now:
| Decision | When | How | |---|---|---| | Source | before | Auto-detect. Ask **only** if detection is genuinely ambiguous (STEP 0). | | Sections | never | Default to **all**. The tier-1 header is the progressive-disclosure layer. | | Format | **after** ASCII | One post-render question (STEP 5), merged with drill-deeper. |
`--quick` skips even that one.
---
**`--quick` skips this whole block.** A 15-second render does not need a dependency graph; the task overhead would cost more than the work.
# 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 sections + dispatch to chosen format(s)", 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. Update status as you progress
TaskUpdate(taskId="2", status="in_progress") # When starting
TaskUpdate(taskId="2", status="completed") # When done — repeat for each subtask# Search for related prior visualizations
mcp__memory__search_nodes(query="plan visualization {PLAN_INPUT}")
# If found, offer to compare with previous plan**First**, attempt auto-detection by running `scripts/detect-plan-context.sh`:
bash "$SK
The Complete AI Development Toolkit for Claude Code. 106 skills, 36 agents, 171 hooks. Install `ork` for stable (v9.x), or `ork-alpha` for the v10 line, which ships daily.
Repo: yonatangross/orchestkit
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