aimem
Skill2 starsChanged 4 days agoApache-2.0View on GitHub
Use when working inside an AIStor Memory workspace — an agent-native FUSE filesystem backed by MinIO AIStor, where reads and writes are ordinary POSIX operations against a remote bucket that outlives the sandbox. Use it whenever `findmnt -S aimem` reports a mount, the working tree has a `.aimem/` directory, or the task mentions AIStor Memory, a Memory Bucket, or keeping agent memory across sessions. Covers locating the mount, when a write is durable, where to keep long-lived agent memory, reading object metadata, annotating objects, and searching the bucket server-side with `aimem search`.
In this repository3 other files it gives its agents.
- docsSkill
- mcSkill
- pr-autofixSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 55
If that project directory is not on the mount, its instruction file is lost with the sandbox: keep the notes on the mount, and tell whoever …
≈ “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.
Files
aimem workspace
You are (or may be) operating inside an AIStor Memory mount: a FUSE filesystem
that backs every read and write to a remote MinIO AIStor bucket. A write is
durable and survives sandbox restart once close() completes its
upload — see references/workspace.md for what is still at risk before that.
Files other agents wrote to the same bucket are visible here too.
Find your mount
This skill is generic — it doesn't know which bucket you're on or where it's mounted. Locate your AIStor Memory mount(s) yourself:
findmnt -n -o TARGET -S aimem # AIStor Memory's mount source is "aimem"; prints the mountpoint path
# portable fallback: mount | sed -n 's/^aimem on \(.*\) type [^ ]* (.*)$/\1/p'The path it reports is your workspace root; the reference docs below call it
<mount-root>. If nothing is reported, no AIStor Memory mount is present in this
environment and this skill does not apply.
Working rules
These hold for every task on the mount. The references explain each in depth.
- A write reaches the bucket when
close()returns success in the process that opened the file. Until then your bytes are only in a local staged copy, and losing the sandbox loses them. A child writing through a descriptor it inherited gets no such guarantee: itsclose()returns before the upload and cannot report a failed one, so open the file in the process that writes and closes it.fsyncflushes that local copy to disk but does not upload it: to checkpoint to the bucket, close the file and reopen it. (On an instruction file that carries the aimem preamble,fsyncdoes upload what you have written so far.) Ifclose()fails, assume the upload did not happen: keep your data and rewrite the whole file with the contents you intended, rather than replaying an append that may already have landed. If another process writes the same file, stop it first and include its changes, or your rewrite removes them. Reading it back through the mount proves nothing, because the mount can still show the bytes it failed to upload. - Keep what the next session needs in the instruction file your agent
loads at startup, in the directory it opens as its project (often the
mount root):
CLAUDE.mdfor Claude Code,AGENTS.mdfor Codex, Cursor and most others. Your context window ends with the sandbox; the mount does not. If that project directory is not on the mount, its instruction file is lost with the sandbox: keep the notes on the mount, and tell whoever starts the next session where they are. A note in any other file is read only if something tells the next session to read it. - Put throwaway output in
/tmp, not the mount. Everything under the mount is uploaded to the bucket. Build output and downloaded archives there cost upload time and fill the bucket. - Work through the mount, not around it. Writing the bucket directly (for
example with
aws s3 cp) bypasses the mount, which then keeps serving stale bytes and can overwrite your change on its next upload. - Keep secrets out of files. Credentials reach the sandbox as environment variables. A key written to the mount is stored in the bucket for every later agent to read.
Which reference to read
The references sit next to this file, under references/. Read one when the
task calls for it:
| When you need to… | Read |
| Find what is at the mount root, or the mount itself | references/navigation.md |
| Know whether a write, rename, chmod or mmap behaves as on local disk, or share a file with another process | references/workspace.md |
| Decide where to save notes, plans or context for a later session | references/memory.md |
| Read an object's S3 metadata or tags | references/metadata.md |
| Leave or read notes on a specific file for other agents | references/annotations.md |
| Find which files mention something, without reading them all | references/search.md |
Annotations are a tech preview and may be off on the server. If a note write fails with "Operation not supported", don't retry it; keep the note in a memory file instead.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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.

