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NotebookLM Distiller
作者
anchor-jevons
· GitHub ↗
· v2.0.0
· MIT-0
372
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install notebooklm-distiller
功能描述
NotebookLM Distiller: Batch knowledge extraction from Google NotebookLM into Obsidian. Supports Q&A generation (15-20 deep questions), structured summaries,...
安全使用建议
This skill appears to implement the described NotebookLM→Obsidian features, but proceed carefully: 1) Review scripts/distill.py locally before enabling — it runs shell commands and writes files. 2) Use a temporary or backup Obsidian vault for first runs to confirm outputs and avoid accidental overwrites. 3) Be aware it requires you to authenticate NotebookLM (notebooklm login creates ~/.book_client_session) and may push distilled notes back into your NotebookLM if you use --writeback. 4) Consider disabling automatic triggers or requiring explicit confirmation before execution (the SKILL.md's 'do NOT ask for clarification' rule is risky). 5) If you use DeepReader integration, verify you trust that other skill because the orchestration can chain actions across skills. If you want, I can point out exact lines in scripts/distill.py to review or produce a safe checklist to sandbox the skill.
功能分析
Type: OpenClaw Skill
Name: notebooklm-distiller
Version: 2.0.0
The notebooklm-distiller skill bundle provides a legitimate set of tools for extracting knowledge from Google NotebookLM into Obsidian. The Python script (distill.py) safely uses subprocess lists to interact with the 'notebooklm' CLI, avoiding shell injection vulnerabilities. The instructions in SKILL.md are focused on task orchestration and do not contain malicious prompt injections or instructions to exfiltrate sensitive data like SSH keys or environment variables.
能力评估
Purpose & Capability
Name/description match the code and required binaries: python3 + notebooklm CLI are reasonable for a NotebookLM→Obsidian distiller. Minor metadata mismatch: registry says 'no install spec' but SKILL.md includes an install recommendation (pip: notebooklm-py). Otherwise the requested tools and files (notebooklm CLI, optional DeepReader integration) are proportionate to the stated purpose.
Instruction Scope
SKILL.md instructs the agent to immediately execute subcommands on trigger phrases and explicitly says 'Do NOT ask for clarification. Execute the appropriate subcommand immediately.' That grants the agent broad discretion and could cause unconfirmed writes. The skill also describes an orchestration path that may call DeepReader (another skill) and instructs running external commands (notebooklm ask --new, notebooklm source add). The script writes files into user-supplied vault paths (including arbitrary --path for persist), so unintended writes / overwrites are possible if triggers are imprecise.
Install Mechanism
No installer in the registry (instruction-only) — lowest risk — but SKILL.md recommends 'pip install notebooklm-py' and requirements.txt lists notebooklm-py, which is consistent. There are no downloads from untrusted URLs or extractable archives in the package. The small inconsistency between registry install metadata and SKILL.md should be clarified, but the actual install steps are standard (pip).
Credentials
The skill declares no required environment variables and needs only the notebooklm CLI + Python, which fits the purpose. In practice it relies on you running 'notebooklm login' (creates ~/.book_client_session) and will therefore use your Google-linked NotebookLM account — that is expected but is sensitive. It may also consult a DeepReader path under ~/.openclaw if present. No unrelated credentials are requested by the skill itself.
Persistence & Privilege
always:false and no system-wide config changes are requested, which is appropriate. However the skill is explicitly capable of writing files into arbitrary directories you point it at (the --vault-dir and --path options) and also offers a --writeback option to push notes back into NotebookLM. That write capability is necessary for the feature but increases risk if triggers run without explicit user confirmation.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install notebooklm-distiller - 安装完成后，直接呼叫该 Skill 的名称或使用
/notebooklm-distiller触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v2.0.0
v2.0: quiz/evaluate for Discord, --lang zh, --writeback to NLM, MIT 48h learning prompts
元数据
常见问题
NotebookLM Distiller 是什么？
NotebookLM Distiller: Batch knowledge extraction from Google NotebookLM into Obsidian. Supports Q&A generation (15-20 deep questions), structured summaries,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 372 次。
如何安装 NotebookLM Distiller？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install notebooklm-distiller」即可一键安装，无需额外配置。
NotebookLM Distiller 是免费的吗？
是的，NotebookLM Distiller 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
NotebookLM Distiller 支持哪些平台？
NotebookLM Distiller 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 NotebookLM Distiller？
由 anchor-jevons（@anchor-jevons）开发并维护，当前版本 v2.0.0。
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