agentleFS
rubixkube-iorubixkube-io/rubixkube-for-ai/skills/environments/SKILL.md

environments

Skill1 starsChanged 36 days agoMITView on GitHub

The organization's sources (Kubernetes clusters, VMs, cloud accounts, connected tools), their health, the environments they are labelled with, and the latest infrastructure snapshot of one source. Use when the person asks what is connected, how one environment is doing, or needs an environment id for another tool.

4 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions4 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 4

    1. robium-ai/robium★ 93same name
    2. quocld/hephaestus-agent-skills★ 8same name
    3. syntropic137/harness-app-template★ 0same name
    4. syntropic137/software-leverage-points★ 0same name

    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.

  • In this repository7 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 4 edited versions we read keep these.

  • 1

    Distinctive

    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
  1. Distinctive:

    Call once per investigation, not repeatedly.

    line 22

“Common” is measured: kept by at least 6 in 10 of the 4 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

When to use

  • "What's connected?" / "Which environments do we have?"
  • "How's the prod cluster?" / "What's running on the staging VM?"
  • Any other tool needs an environment_id.

Tools

  • list_environments(): id, name, kind (kubernetes, vm, aws, gcp, azure, or a connected tool), status, last heartbeat, and the environment labels (staging, production).
  • environment_snapshot(environment_id): the latest snapshot of one source. Nodes, workloads and their status for Kubernetes; host metrics, processes and services for a VM. Call once per investigation, not repeatedly.

How to answer

Name sources by their name, not their id, and say which environment label they carry. A source whose last heartbeat is old is likely disconnected: say so plainly. For incidents in one environment, pass its id or name to list_incidents.

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Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

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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.