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ljg-skill-map▌

lijigang/ljg-skills · updated Apr 8, 2026

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$npx skills add https://github.com/lijigang/ljg-skills --skill ljg-skill-map
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summary

扫描 ~/.claude/skills/ 下所有已安装技能，生成一目了然的可视化地图。

skill.md

ljg-skill-map: 技能地图

扫描 ~/.claude/skills/ 下所有已安装技能，生成一目了然的可视化地图。

执行

1. 扫描

运行 scripts/scan.sh，获取所有技能的 JSON 数据（name, version, invocable, desc）。

2. 分类

根据技能名称和描述，将技能自动归入以下类别：

类别 图标 含义 典型成员
认知原子 ◆ 内容处理的原子操作 ljg-plain, ljg-word, ljg-writes, ljg-paper
输出铸造 ▲ 将内容转化为可交付物 ljg-card
联网触达 ● 与外部世界交互 agent-reach
系统运维 ■ Agent 自身的维护和管理 datetime-check, memory-review, save-conversation, skill-creator, ljg-skill-map
环境部署 ★ 一次性安装和配置 Her-init

归类依据名称前缀和描述关键词判断。遇到新技能无法归类时，放入「未分类」。

3. 渲染

用 ASCII 方框图呈现，格式如下：

╔══════════════════════════════════════════════════════════╗
║              SKILL MAP  ·  {N} skills installed         ║
╠══════════════════════════════════════════════════════════╣
║                                                          ║
║  ◆ 认知原子                                              ║
║  +-----------------+----------------------------------+  ║
║  | ljg-plain v4.0  | 白 — 好问题+类比让人 grok        |  ║
║  | ljg-word  v1.0  | 英文单词深度拆解                  |  ║
║  | ljg-writes v4.0 | 写作引擎                          |  ║
║  | ljg-paper v2.0  | 论文阅读与分析                    |  ║
║  +-----------------+----------------------------------+  ║
║                                                          ║
║  ▲ 输出铸造                                              ║
║  +-----------------+----------------------------------+  ║
║  | ljg-card  v1.5  | 铸 — 内容转 PNG 可视化           |  ║
║  +-----------------+----------------------------------+  ║
║                                                          ║
║  ...                                                     ║
╚══════════════════════════════════════════════════════════╝

规则：

  • 每个类别一个区块，类别图标 + 中文名做标题
  • 技能名左对齐，版本号紧跟（无版本显示 -）
  • 描述截断到一行，保留核心语义
  • user_invocable 为 true 的技能名后加 / 标记（表示可直接 /技能名 调用）
  • 底部统计行：总数、可调用数、分类数

4. 输出

直接在对话中渲染 ASCII 地图。不生成文件，不写入磁盘。

how to use ljg-skill-map

How to use ljg-skill-map on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add ljg-skill-map
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/lijigang/ljg-skills --skill ljg-skill-map

The skills CLI fetches ljg-skill-map from GitHub repository lijigang/ljg-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ljg-skill-map

Reload or restart Cursor to activate ljg-skill-map. Access the skill through slash commands (e.g., /ljg-skill-map) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client
  • ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • ›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • ⚠Not validating competitive research—verify facts before sharing
  • ⚠Accepting user stories without involving engineering team
  • ⚠Over-relying on frameworks without qualitative judgment
  • ⚠Not customizing outputs to company culture and communication style
  • ⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • −Don't publish competitive analysis without fact-checking
  • −Don't finalize user stories without engineering review
  • −Don't make prioritization decisions solely on AI scoring
  • −Don't skip customer validation of generated requirements
  • −Don't ignore company-specific context and culture

💡 Pro Tips

  • ★Provide context: company goals, constraints, customer feedback
  • ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • ★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.5★★★★★56 reviews
  • ★★★★★Ganesh Mohane· Dec 28, 2024

    ljg-skill-map is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★James Brown· Dec 16, 2024

    Registry listing for ljg-skill-map matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Amelia Harris· Dec 16, 2024

    ljg-skill-map fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Rahul Santra· Nov 19, 2024

    Useful defaults in ljg-skill-map — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Amelia Taylor· Nov 7, 2024

    ljg-skill-map reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★James Taylor· Nov 7, 2024

    We added ljg-skill-map from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Amelia Martin· Oct 26, 2024

    ljg-skill-map is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Nikhil Rao· Oct 26, 2024

    Keeps context tight: ljg-skill-map is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Pratham Ware· Oct 10, 2024

    Registry listing for ljg-skill-map matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Hiroshi Dixit· Sep 25, 2024

    ljg-skill-map fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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