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Agent Skill · 研究检索

visualize-plan(可视化计划)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

visualize-plan 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 39,716。

总安装 1,373周安装 55GitHub Stars 161下载 444核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:visualize-plan(可视化计划)
来源仓库:https://github.com/yonatangross/orchestkit
仓库路径:skills/visualize-plan
安装命令:
npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。适合根据产品场景整理页面结构、生成 UI 方案或检查视觉一致性。使用时需结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及页面改动时应通过截图或浏览器预览检查表现。

安装命令:npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan 注意:涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

来源仓库内路径:skills/visualize-plan

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

visualize-plan 怎么安装?

在终端执行 npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

visualize-plan 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

visualize-plan 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

visualize-plan 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

visualize-plan 用的人多吗?

公开数据是累计安装 1,373 次,近一周安装 55 次,下载 444 次,GitHub 161 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

visualize-plan 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
visualize-plan

可视化计划 · 本页

1,373161执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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:

SectionReferenceKey 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.

SectionWhat It ShowsReference
[6] Blast RadiusConcentric rings of impact (direct -> transitive -> tests)(load ${CLAUDE_SKILL_DIR}/references/blast-radius-patterns.md)
[7] Cross-Layer ConsistencyFrontend/backend endpoint alignment with gap detection(load ${CLAUDE_SKILL_DIR}/references/deep-dives.md)
[8] Migration ChecklistOrdered runbook with sequential/parallel blocks and time estimates(load ${CLAUDE_SKILL_DIR}/references/deep-dives.md)

Key Principles

PrincipleApplication
Progressive disclosureTier 1 header always, sections on request
Judgment over decorationEvery section answers a reviewer question
Precise over estimatedUse scripts for file/line counts
Honest uncertaintyConfidence levels, pre-mortems, tradeoff costs
Actionable outputWrite to file, generate issues, drill deeper
Anti-slopNo generic transitions, no fake precision, no unused sections

Rules Quick Reference

RuleImpactWhat It Covers
section-rendering (load ${CLAUDE_SKILL_DIR}/rules/section-rendering.md)HIGHRendering conventions for all 5 core sections
ASCII diagramsMEDIUMVia ascii-visualizer skill (box-drawing, file trees, workflows)

References

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

FileContent
visualization-tiers.mdProgressive disclosure tiers and header field computation
change-manifest-patterns.mdChange manifest ASCII patterns
execution-swimlane-patterns.mdExecution swimlane ASCII patterns
risk-dashboard-patterns.mdRisk dashboard ASCII patterns
decision-log-patterns.mdDecision log ASCII patterns
blast-radius-patterns.mdBlast radius ASCII patterns
deep-dives.mdCross-layer consistency and migration checklist

Assets

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

FileContent
plan-report.mdFull mustache-style report template
impact-dashboard.mdImpact table template
tier1-header.md5-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

平台分布

Codex

38.03%
按下载量换算169

Claude

28.92%
按下载量换算128

Cursor

19.89%
按下载量换算88

Gemini CLI

8.93%
按下载量换算40

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/yonatangross/orchestkit --skill visualize-plan 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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