Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nainsharma01/claude-code-visualizer/agent-skill-visualizernpx skills add nainsharma01/claude-code-visualizer --skill agent-skill-visualizergit clone --depth 1 https://github.com/nainsharma01/claude-code-visualizerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nainsharma01/claude-code-visualizer/agent-skill-visualizer)<a href="https://agentmods.dev/skills/nainsharma01/claude-code-visualizer/agent-skill-visualizer"><img src="https://agentmods.dev/badge/skills/nainsharma01/claude-code-visualizer/agent-skill-visualizer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.00644 |
| Opus 5 | $0.00027 | $0.00322 |
| Sonnet 5 | $0.00011 | $0.00129 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
agent-skill-visualizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Agent-Skill Visualizer
Claude Code 프로젝트의 .claude/ 폴더 구조를 분석하여 에이전트와 스킬 간의 관계를 인터랙티브한 노드 그래프로 시각화합니다.
사용 시점
- "에이전트 구조 보여줘"
- "스킬 의존성 확인해줘"
- "에이전트와 스킬 관계 시각화해줘"
- "프로젝트 구조 그래프로 보고 싶어"
실행 방법
1. 데이터 생성 (Python 스캐너)
cd .claude/skills/agent-skill-visualizer
# 현재 프로젝트 스캔
python scripts/scan_agents_skills.py ../../../ --output webapp/public/data/graph-data.json
# 다른 프로젝트 스캔
python scripts/scan_agents_skills.py /path/to/other/project --output graph-data.json
2. 웹앱 실행
cd webapp
npm install
npm run dev
# → http://localhost:5173
3. 빌드 후 배포
npm run build
# dist/ 폴더에 정적 파일 생성
npx serve dist
기능
- 노드 그래프: D3.js force-directed 레이아웃
- 드래그 & 줌: 노드 위치 조정, 확대/축소
- 노드 타입: 🤖 Agent (파란색), 🔧 Skill (초록색)
- 연결 타입: uses (실선), depends (점선)
- 검색: 노드 이름/설명으로 필터링
- 상세 패널: 노드 클릭 시 메타데이터 표시
범용성
이 스킬은 다른 Claude Code 프로젝트에서도 사용할 수 있습니다:
- 스킬 폴더를 복사:
cp -r agent-skill-visualizer /new/project/.claude/skills/ - 데이터 생성:
python scripts/scan_agents_skills.py /new/project - 웹앱 실행:
cd webapp && npm run dev
출력 데이터 형식
{
"nodes": [
{ "id": "agent:name", "type": "agent", "name": "...", ... },
{ "id": "skill:name", "type": "skill", "name": "...", ... }
],
"edges": [
{ "source": "agent:x", "target": "skill:y", "type": "uses" }
],
"metadata": {
"projectName": "...",
"agentCount": 5,
"skillCount": 6
}
}
What ships with it
25 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 3.0 KB
- scripts/scan_agents_skills.py 13 KB runs code
- scripts/stream_server.py 11 KB runs code
- webapp/index.html 673 B
- webapp/package-lock.json 113 KB
- webapp/package.json 749 B
- webapp/postcss.config.js 80 B runs code
- webapp/src/App.tsx 23 KB
- webapp/src/components/BezierEdge.tsx 2.4 KB
- webapp/src/components/CallStack.tsx 2.2 KB
- webapp/src/components/CommandBuilder.tsx 6.8 KB
- webapp/src/components/DetailPanel.tsx 7.3 KB
- webapp/src/components/Legend.tsx 4.3 KB
- webapp/src/components/NodeCard.tsx 5.8 KB
- webapp/src/components/SearchBar.tsx 1.4 KB
- webapp/src/hooks/code-visualizer-claude-v2.9-beta.3.zip 1365 KB
- webapp/src/hooks/useActivityStream.ts 2.7 KB runs code
- webapp/src/hooks/useGraphData.ts 1.3 KB runs code
- webapp/src/main.tsx 237 B
- webapp/src/styles/index.css 2.7 KB
- webapp/src/types/graph.ts 1.6 KB runs code
- webapp/tailwind.config.js 434 B runs code
- webapp/tsconfig.json 562 B
- webapp/tsconfig.node.json 213 B
- webapp/vite.config.ts 254 B runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 83 lines · 54 tokens per session scan A 159eeec8dddc
agent-skill-visualizer is a skill published in the GitHub repository nainsharma01/claude-code-visualizer (5 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 644 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
crewai
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative…
context7-auto-research
Automatically fetch latest library/framework documentation for Claude Code via Context7 API.
deep-research-notebooklm
Deep research skill powered by NotebookLM MCP. Conducts structured multi-source research (market analysis, competitive intel, trend analysis, prospect research) using Google NotebookLM as the research engine, then delivers formatted briefs and optional studio artifacts (slides, audio podcasts, videos, infographics…
r3f-animation
React Three Fiber animation - useFrame, useAnimations, spring physics, keyframes. Use when animating objects, playing GLTF animations, creating procedural motion, or implementing physics-based movement.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
agile-product-owner
../../../product-team/agile-product-owner/skills/agile-product-owner/SKILL.md.