Updated 7mo ago
by xvirobotics
metaskill
Metaskill: A Meta-Skill for Autonomous AI Agent Team Generation
73 GitHub stars (73)
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- 9 skills (9 skills found in its SKILL.md files)
- 11 forks (11 forks)
- 7mo ago last update (Last updated 7mo ago)
Install
Skills CLI
npx skills add xvirobotics/metaskill
Asks which skills and agents to install. Just one: npx skills add xvirobotics/metaskill --skill metaskill — add -g for every project.
Claude Code
git clone https://github.com/xvirobotics/metaskillcp -r "metaskill/skill" ~/.claude/skills/
Copies the metaskill skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add xvirobotics/metaskill
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md.
-
metaskill
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/SKILL.md on GitHub (opens in a new tab) -
flows
No description in the SKILL.md.
skill/flows/skill.md on GitHub (opens in a new tab) -
evaluate-model
Load the latest model checkpoint, run evaluation on the test set, and generate a metrics report with confusion matrix. Use this after training to assess model performance or to re-evaluate a specific checkpoint.
examples/data-science/.claude/skills/evaluate-model/SKILL.md on GitHub (opens in a new tab) -
generate-report
Generate a comprehensive summary report of the latest experiment including metrics, plots, and comparison with baseline. Use this after training and evaluation to create a shareable experiment summary.
examples/data-science/.claude/skills/generate-report/SKILL.md on GitHub (opens in a new tab) -
run-pipeline
Run the full data science pipeline: validate raw data, preprocess, engineer features, train model, and evaluate. Use this when you want to execute the end-to-end ML pipeline or re-run it after data or code changes.
examples/data-science/.claude/skills/run-pipeline/SKILL.md on GitHub (opens in a new tab) -
api-test
Run API integration tests against the running backend, verify endpoints return expected responses and status codes. Use after deploying a preview or starting the dev server.
examples/fullstack-web/.claude/skills/api-test/SKILL.md on GitHub (opens in a new tab) -
build-and-test
Install dependencies, run type checking, lint, tests, and build the project. Use after making code changes to verify nothing is broken.
examples/fullstack-web/.claude/skills/build-and-test/SKILL.md on GitHub (opens in a new tab) -
deploy-preview
Build Docker images and launch a local preview environment with docker-compose. Use to test the full stack locally before merging.
examples/fullstack-web/.claude/skills/deploy-preview/SKILL.md on GitHub (opens in a new tab) -
run-simulator
Build and launch the app in the iOS Simulator. Automatically selects an appropriate simulator device, boots it if needed, and installs and launches the app.
examples/ios-app/.claude/skills/run-simulator/SKILL.md on GitHub (opens in a new tab)
No skill matches that filter.
Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.
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