notebooklm-ingest
Skill2 starsChanged 58 days agoLicence not identifiedView on GitHub
Front door for multi-source synthesis into the wiki: when several sources (YouTube, articles, PDFs) should become one wiki entry, this offloads synthesis to Google's NotebookLM, downloads the report to .raw/notebooklm/ (source_type: research-report), then hands off to ingest — no manual copy-paste. Prefer this over the one-at-a-time fetchers when the user gives many links to combine. Two modes: CREATE a new notebook from URLs, or PULL an existing notebook you already curated. Triggers on: notebooklm, notebooklm ingest, notebooklm pull, synthesize these sources, add these sources to my wiki, ingest these urls together, combine these links into a wiki page, research report from these links, make a wiki page from these links, notebook from urls, pull my notebook, batch analyze sources.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .cursor/rules/techtrip-secondbrain.mdcCursor rule
- brain-dumpSkill
- code-fetchSkill
- mode-fitSkill
- new-ideaSkill
- secondbrain-doctorSkill
- secondbrainSkill
- voice-fetchSkill
- x-fetchSkill
- yt-fetchSkill
The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
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