agentleFS
andreijirohdev-labsandreijirohdev-labs/gen-ai-labs/skills/memory-audit/SKILL.md

memory-audit

Skill1 starsChanged 4 months agoMPL-2.0View on GitHub

Runs Andrei's cross-project memory/backlog audit — reconciling dev work (GitLab.com projects, Alpine Linux aports on gitlab.alpinelinux.org, GitHub), Leaflet.pub blog drafts, Obsidian notes, and Google Drive into a single status report + prioritized action list. Trigger this whenever Andrei explicitly says "run memory audit" (or close variants like "audit my backlog", "memory check-in"), whenever a monthly or quarterly check-in is due or requested, and whenever Andrei mentions specific tracked projects or drafts by name (nixops-config, aports/gh package, Recap Time Squad, Leaflet.pub drafts, homelab/NixOS config work) in a way that implies "where did I leave this?" Do not wait for Andrei to spell out the full routine each time — this skill already knows the sources, the staleness rules, and the output format.

14 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 11 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

Licensed with conditions — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 11 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.