agentleFS
arnaugonzalezarnaugonzalez/memory-boost/skills/save-session/SKILL.md

save-session

Skill0 starsChanged 47 days agoMITView on GitHub

Save what was done in this session to the shared agent memory (log entry + project page update) so any other agent or harness can pick it up later. Use when the user says "save session", "log this session" or "save to memory", or at the end of significant work.

19 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use status and ship.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • AnthropicSkill

    status

    Case status summary by audience — client-facing (plain language), internal (for the professor), or court-ready (formal caption format per local rules). Same facts, different framing and depth. Use when a student needs to update the client, brief the professor, or prepare a court status report.

    Also in 3 projects that use this

  • AWSSkill

    ship

    Finalize dev work on an issue branch — update docs, push, and open a PR.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

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

  • 0

    Common

    Most of the 18 edited versions we read keep these.

  • 1

    Distinctive

    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
  1. Very specific:

    If the session produced stable knowledge (how to run the project, an architecture fact, a gotcha that will bite again), edit …

    line 12
  2. Very specific:

    If a decision was made, create wiki/decisions/<slug>.md with frontmatter status: current and review_by: <date>.

    line 15
  3. Very specific:

    If you used checkpoints, close yours: memory_checkpoint(..., status="done").

    line 17
  4. Distinctive:

    If the memory home is a git repository, commit only if the user asked you to.

    line 18

“Common” is measured: kept by at least 6 in 10 of the 18 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

save-session

  1. Identify the project slug (the directory name, or ask if unclear).
  2. Summarise the session: one-line action, one detail sentence with the key result, and pending if something is left to do. Facts only; no narrative.
  3. Call memory_save(project, action, detail, pending, agent="<your harness name>").
  4. If the session produced stable knowledge (how to run the project, an architecture fact, a gotcha that will bite again), edit wiki/projects/<project>.md directly and add it under the right ## section. Do not copy the log into the page.
  5. If a decision was made, create wiki/decisions/<slug>.md with frontmatter status: current and review_by: <date>; mark the decision it replaces status: superseded.
  6. If you used checkpoints, close yours: memory_checkpoint(..., status="done").
  7. If the memory home is a git repository, commit only if the user asked you to.

Download now (ZIP)

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.