agentleFS
Sign inStart free
jabrenajabrena/cursor-rules-java/skills/005-agents-installation/SKILL.md

005-agents-installation

Skill452 starsChanged 3 months agoApache-2.0View on GitHub

Use when you need to install the embedded robot agents into .github/agents, .claude/agents, .cursor/agents, or .codex/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .github/agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Bootstrap .codex/agents; Copy robot agents. Part of Plinth Toolkit

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    MUST: ask the user to choose .github/agents, .claude/agents, .cursor/agents, or .codex/agents before installing

    line 23
  2. Very specific:

    Ask exactly one question to choose .github/agents, .claude/agents, .cursor/agents, or .codex/agents and wait for an explicit answer before …

    line 40
  3. Distinctive:

    Do not copy any file until destination is explicitly confirmed

    line 43
  4. Distinctive:

    If destination is ambiguous, ask a clarification question

    line 44
  5. Distinctive:

    Create the destination directory if needed, then copy all embedded agent files defined in the reference content, preserving filenames and …

    line 48

≈ “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.

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

Embedded agents installer

Install a predefined set of embedded agent definitions from repository assets into a user-selected target directory. This is an interactive skill.

What is covered in this Skill?

  • Interactive target selection (.github/agents, .claude/agents, .cursor/agents, or .codex/agents)
  • Deterministic copy of all embedded agents defined via XInclude from assets/agents
  • Idempotent re-installation with clear overwrite reporting

Constraints

This skill installs only the embedded robot agents bundle and must ask for destination before writing files.

  • MUST ask the user to choose .github/agents, .claude/agents, .cursor/agents, or .codex/agents before installing
  • MUST copy all embedded agent files defined in references/005-agents-installation.md
  • MUST preserve file names from the reference content and report overwrite actions

When to use this skill

  • Install embedded agents
  • Bootstrap .github/agents
  • Bootstrap .cursor/agents
  • Bootstrap .claude/agents
  • Bootstrap .codex/agents
  • Copy robot agents

Workflow

  1. Choose destination

Ask exactly one question to choose .github/agents, .claude/agents, .cursor/agents, or .codex/agents and wait for an explicit answer before copying files.

Step constraints:

  • Do not copy any file until destination is explicitly confirmed
  • If destination is ambiguous, ask a clarification question
  1. Install embedded agents

Create the destination directory if needed, then copy all embedded agent files defined in the reference content, preserving filenames and warning before overwriting existing files.

  1. Report installation result

Return a concise checklist with selected destination, created/updated files, overwrite actions, and an optional verification command.

Reference

For detailed guidance, examples, and constraints, see references/005-agents-installation.md.

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.

Check your setup, free