Borrowing it
Nothing to install: this file belongs to capitalparser/notebooklm-wiki-pipeline. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/capitalparser/notebooklm-wiki-pipeline/main/CLAUDE.mdgit clone --depth 1 https://github.com/capitalparser/notebooklm-wiki-pipelineWrote 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/instructions/capitalparser/notebooklm-wiki-pipeline/claude-md)<a href="https://agentmods.dev/instructions/capitalparser/notebooklm-wiki-pipeline/claude-md"><img src="https://agentmods.dev/badge/instructions/capitalparser/notebooklm-wiki-pipeline/claude-md.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 5.1 | $0.00571 | $0.00571 |
| Opus 5 | $0.00285 | $0.00285 |
| Sonnet 5 | $0.00114 | $0.00114 |
| Haiku 4.5 | $0.00057 | $0.00057 |
Grade A, and why
notebooklm-wiki-pipeline CLAUDE.md 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 8d 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
05_notebooklm_wiki_pipeline — 프로젝트 컨텍스트
Drive 대용량 PDF를 NotebookLM에 외주화하고, 분석 결과만 Claude Code가 수령하여 00_Wiki/ Obsidian 노트로 자동 변환하는 토큰-효율 파이프라인.
핵심 문제
Drive MCP로 PDF를 직접 읽으면 PDF 전체 텍스트가 Claude 컨텍스트를 지나가 토큰 소모가 과다. NotebookLM이 내부에서 PDF를 처리하고 Claude는 분석 결과(텍스트)만 수령하는 구조로 해결.
아키텍처
Drive PDF (대용량)
↓ source_add(drive_url) — URL만 전달, 파일 내용은 Claude 컨텍스트 비통과
NotebookLM 내부 처리
↓ notebook_query("분석 요청")
분석 결과 텍스트 — 수백~수천 토큰만
↓ Claude Code 구조화
00_Wiki/{category}/{title}.md — [[wikilink]] 포함 Obsidian 노트
도구 구성
- notebooklm-mcp-cli (PyPI):
notebooklm-mcpMCP 서버- 설치:
uv tool install notebooklm-mcp-cli - 인증:
nlm login(브라우저 기반 쿠키, 2-4주 유효) - MCP 등록:
nlm setup add claude-code
- 설치:
- Drive MCP (
mcp__claude_ai_Google_Drive__*): 파일 메타데이터/ID 조회용만 사용download_file_content사용 금지 — 토큰 낭비의 원인
슬래시 커맨드
/pdf-to-wiki— 단일 PDF → Obsidian 노트 변환- 플러그인 위치:
~/.claude/commands/pdf-to-wiki.md - Claude Code 세션 시작 시 자동 로드됨
- 플러그인 위치:
인증 관리
NotebookLM 쿠키는 2-4주마다 만료. 만료 시:
nlm login
자동 갱신 시도하지만 실패 시 수동 재인증 필요. Free tier: ~50 queries/day 한도.
산출물 위치
- 생성 노트:
~/vault/00_Wiki/AI_Generated/ - 재사용 노트북: NotebookLM 웹 UI에서 확인 가능 (쿼리 기록 자동 동기화)
ADR
- 0001-notebooklm-mcp-approach.md — NotebookLM vs Gemini API 선택 근거
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.
- 8d ago First seen · 55 lines · 571 tokens per session scan A 34ed853423ee
notebooklm-wiki-pipeline CLAUDE.md is an instructions file published in the GitHub repository capitalparser/notebooklm-wiki-pipeline (93 stars, last pushed 3mo ago), licensed MIT. It adds 571 tokens to every session, about $0.0029 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 2026-08-30.
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