personal-notes
Skill617 starsChanged 10 months agoMITView on GitHub
Search, read, create, and carefully edit Markdown notes in a user-mounted Obsidian vault or Bear export
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 6 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
Ask for the exact mounted vault or export path when it is not already explicit in the conversation or workspace configuration.
- Very specific: line 20
Use a narrow glob, list_directory, or grep under that root.
- Distinctive: line 24
Search titles, tags, links, and content, then read only the most relevant notes.
- Very specific: line 27
Do not ingest an entire vault into memory by default.
- Very specific: line 33
Prefer a targeted edit_file operation for an existing note.
- Distinctive: line 34
Never overwrite a note to append a small section, never silently rename or move notes, and never resolve link conflicts by deleting content.
- Distinctive: line 35
After a write, state the path and what changed.
- Distinctive: line 39
If the vault is not mounted, tell the user to mount or copy it into the Hexis workspace and provide that path.
- Distinctive: line 41
If writes are disallowed, provide the ready-to-paste Markdown and exact intended path so the work remains useful.
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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.
Files
Personal Notes
Work with notes the user intentionally exposes inside the Hexis workspace. This supports Markdown-based Obsidian vaults and exported Bear notes; it does not reach into an unmounted home directory or Bear's private live database.
Establish the Note Root
- Ask for the exact mounted vault or export path when it is not already explicit in the conversation or workspace configuration.
- Confirm that the path is inside the permitted workspace. Never guess a path, scan the user's home directory, or reuse an unrelated repository because it happens to contain Markdown.
- Use a narrow
glob,list_directory, orgrepunder that root. Expand the search only when the initial results justify it.
Read and Search
- Search titles, tags, links, and content, then read only the most relevant notes.
- Cite note paths in the answer so the user can locate the source.
- Preserve the distinction between text in a note, a Hexis memory, and the assistant's inference.
- Do not ingest an entire vault into memory by default. Use
fast_ingestonly for files the user explicitly chooses and explain that it creates derived memories.
Create and Edit
- Resolve the exact target path and inspect any existing file before proposing a change.
- Preserve YAML frontmatter, tags, wiki links, embeds, heading style, and surrounding formatting.
- Prefer a targeted
edit_fileoperation for an existing note. For a new note, show the proposed path and content beforewrite_fileunless the user's request already specified both. - Never overwrite a note to append a small section, never silently rename or move notes, and never resolve link conflicts by deleting content.
- After a write, state the path and what changed. If the tool reports a failure, do not claim the note was saved.
No Dead Ends
- If the vault is not mounted, tell the user to mount or copy it into the Hexis workspace and provide that path.
- For Bear, request a Markdown export or mounted export directory; do not advise modifying Bear's internal database.
- If writes are disallowed, provide the ready-to-paste Markdown and exact intended path so the work remains useful.
Other versions1 project uses a version of this.
Word for word · 1
- QuixiAI/Hexis★ 617100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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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.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

