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Updated 1mo ago

by a-tokyo

aiworkspace

🧑 💻 Set up and manage AI agent skills and configs for Cursor, Claude Code, Codex and more across multi-repo workspaces.

  • Multi-agent — Targets three or more agents
Works with
  • Claude
  • Codex
  • Cursor
  • Gemini
  • Copilot
  • OpenCode
View on GitHub (opens in a new tab)

21 GitHub stars (21)

+1 in 16 days

Stars gained per day · daily snapshots since Sep 30
Stars gained per day, Sep 30 to Oct 16: +1 in total; the busiest day was Oct 1 with +1 stars.Oct 1: +1 starsOct 2: 0 starsOct 3: 0 starsOct 4: 0 starsOct 5: 0 starsOct 6: 0 starsOct 7: 0 starsOct 8: 0 starsOct 9: 0 starsOct 10: 0 starsOct 11: 0 starsOct 12: 0 starsOct 13: 0 starsOct 14: 0 starsOct 15: 0 starsOct 16: 0 stars
Stars gained between daily snapshots
PeriodNew stars
Oct 1+1
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  • 4 skills (4 skills found in its SKILL.md files)
  • 5 forks (5 forks)
  • 1mo ago last update (Last updated 1mo ago)

Install

Skills CLI

npx skills add a-tokyo/aiworkspace

Asks which skills and agents to install. Just one: npx skills add a-tokyo/aiworkspace --skill autoresearch — add -g for every project.

Claude Code

git clone https://github.com/a-tokyo/aiworkspacecp -r "aiworkspace/.agents/skills/autoresearch" ~/.claude/skills/

Copies the autoresearch skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.

Plugin

/plugin marketplace add a-tokyo/aiworkspace

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.

  • autoresearch

    Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, auto…

    .agents/skills/autoresearch/SKILL.md on GitHub (opens in a new tab)

  • production-grade

    Principle-engineering posture for production-grade code: reads the repo first, plans before code, matches conventions, pulls latest docs over training recall, and ships the simplest correct change that holds the bar — proper algorithms and data structures, idempotent writes, schema+queries+indexes as one artefact, typed errors, tests in the same diff. Substrate-agnostic; defers to peer skills on…

    .agents/skills/production-grade/SKILL.md on GitHub (opens in a new tab)

  • tribunal

    Runs a doer -> verifier-panel -> consensus loop to verify a deliverable before it ships. An orchestrator freezes acceptance criteria before implementation, dispatches a doer, then convenes a context-walled panel of independent verifiers - including an adversary with an explicit must-oppose mandate - for evidence-anchored review adjudicated to a SHIP / SHIP_WITH_CAVEATS / ITERATE / BLOCK / ESCALAT…

    .agents/skills/tribunal/SKILL.md on GitHub (opens in a new tab)

  • scaffold-skill

    Scaffold new AI agent skills with proper symlinking across all IDE tools (Cursor, Claude Code, Codex, etc.). Use when creating a new skill, adding a local skill, or when the user wants to write a custom skill -- either workspace-wide or for a specific project.

    root-config/.agents/skills/scaffold-skill/SKILL.md on GitHub (opens in a new tab)

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.