agentsclimarketplace

Skill

Skill xvirobotics/metaskill/skill

Metaskill: A Meta-Skill for Autonomous AI Agent Team Generation

Install
npx -y skills add xvirobotics/metaskill --skill skill

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

The meta-skill: create AI agent teams, individual agents, or custom skills for any project. Use when the user wants to generate a complete .claude/ agent team, create a single agent, or create a single skill.

SKILL.md

2.4 KB, 490 tokens by cl100k_base, as published. Nobody here has run it

You are an elite AI agent architect. You can create complete agent teams, individual agents, or custom skills — all through a single command.

User request: $ARGUMENTS

Auto-Detected Context

Working directory: !pwd Existing subdirectories: !ls -d */ 2>/dev/null | head -20 || echo "empty directory" Skill base: !for d in "$HOME/.claude/skills/metaskill" ".claude/skills/metaskill"; do [ -d "$d/flows" ] && echo "$d" && break; done 2>/dev/null || echo "$HOME/.claude/skills/metaskill"

Step 1: Detect Intent

Analyze $ARGUMENTS to determine the mode:

  • Team mode (default): The user wants a complete agent team for a project type. Trigger words: "app", "project", "team", "fullstack", "pipeline", "game dev", or any domain/technology without explicit "agent" or "skill" keywords. Examples: "ios app", "fullstack web", "data science pipeline", "game dev with Unity"

  • Agent mode: The user wants to create a single agent. Trigger words: "agent", "reviewer", "engineer" (as a role), or phrases like "create an agent that..." Examples: "a security reviewer agent", "code reviewer for Go", "create an agent that handles deployments"

  • Skill mode: The user wants to create a single skill (slash command). Trigger words: "skill", "command", "slash command", or phrases like "create a skill that..." Examples: "a deploy skill", "slash command to run tests", "create a skill for linting"

If the intent is ambiguous, use AskUserQuestion to ask the user which mode they want.

Step 2: Load and Execute Flow

Based on the detected mode, read the corresponding flow file from the Skill base path detected above:

  • Team mode → Read <skill-base>/flows/team.md
  • Agent mode → Read <skill-base>/flows/agent.md
  • Skill mode → Read <skill-base>/flows/skill.md

Then follow the instructions in that flow file exactly, using the user's request as context.

Gives 0 of the 12 instructions most context ai engineering skills give in 490 tokens

Counted across 1,193 of the 1,976 authors here whose files we hold, read 2026-08-06

  • dispatch a fresh implementer subagent per taskin 48 of 1193, across 19 files
  • dispatch final reviewer after all tasksin 37 of 1193, across 11 files
  • provide full task text to the subagentin 31 of 1193, across 10 files
  • review spec compliance before code qualityin 27 of 1193, across 10 files
  • make the hook script executablein 26 of 1193, across 8 files
  • re-snapshot after navigation or DOM changesin 25 of 1193, across 17 files
  • answer subagent questions before proceedingin 22 of 1193, across 7 files
  • mark task complete in TodoWrite after approvalin 22 of 1193, across 6 files
  • merge hook into existing settingsin 21 of 1193, across 3 files
  • read files before editing themin 21 of 1193, across 9 files
  • ask if installation is global or projectin 20 of 1193, across 2 files
  • copy the hook script to target locationin 20 of 1193, across 2 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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