A Claude Code plugin marketplace of the skills we share at AI Builder Club for building loop engineers: agents that get triggered on their own, pick up work, ship it, verify it, and log what they learned, so the work compounds without you prompting every step. It's the productized version of the setup my team runs in production.

Two flagship skill sets (more to come):

• Codebase harness — make any repo agent-ready (run, test, verify, ship — including an isolated cloud box per agent so loops ship code in parallel).
• Loops — spin up compounding agent loops on a shared, file-based knowledge base.

The shift: you stop prompting a coding agent task-by-task, and start designing loops.

A loop is an agent that wakes up on a trigger (a cron, a webhook, an incident, another agent), does some investigation and work, and writes what it found and did into a shared, file-based memory. Next run it reads that memory and keeps going. The real power is compounding: many loops (support, SEO, product, ads) read and write the same folders, so a friction the support loop logs can get picked up by the product loop, and a keyword the ads loop finds can feed the SEO loop. One shared brain, many loops.

Building one comes down to four ingredients:

1. Triggers: cron, webhook, an incident, or another agent wakes the loop at the right time.
2. A file + logging structure: the shared memory loops read and write → the loops plugin.
3. Tools & connectors: so the agent can do real work (your skills/MCPs).
4. A codebase harness: so the agent can run, test, and verify its own work → the codebase-harness plugin.

These plugins give you #2 and #4, plus the scaffolding to add the rest.

Want the full walkthrough of the concept and how my team designs compounding loops? Watch the video:

/plugin marketplace add AI-Builder-Club/skills
/plugin install skills@ai-builder-club

One plugin, all the skills below.

Run it in the code repo your agents work in, so they can run, test, and verify their own work. It orchestrates the harness skills below — pull in only what the repo needs.

Run it where your agent's memory should live. First run bootstraps the knowledge base (creates ARCHITECTURE.md, LOG.md, the signals/ docs/ domains/ folders, and a knowledge-base section in your CLAUDE.md); then it scaffolds the loop, does one real test run, and logs it. Run it again any time to add another loop.

Codebase harness — make a repo agent-ready

Loops — the shared knowledge base

After setup, each session the agent reads CLAUDE.md + the relevant domain README, does work, writes artifacts, and appends to LOG.md. For code changes it drives ship-change and ships via /pr.

• Claude Code (the skills assume it).
• git. That's the only hard dependency for the knowledge base + harness.
• The harness skills want the code repo they ship into to be a git repo with a working build/test setup. They use Codex for review if available, and degrade gracefully if not.
• crabbox-setup (optional, for parallel cloud boxes) needs the crabbox CLI + a provider (Daytona: daytona CLI / DAYTONA_API_KEY).

skills/                                a Claude Code plugin (also a marketplace)
├── .claude-plugin/
│   ├── marketplace.json              marketplace: ai-builder-club
│   └── plugin.json                   plugin: skills   (source ".")
└── skills/                           top-level skills
    ├── new-loop/                     (loops) — + references/: ARCHITECTURE · LOG · KNOWLEDGE_SETUP · CLAUDE.template
    ├── setup-codebase-harness/       (harness) — orchestrator
    ├── dev-local-setup/              (harness)
    ├── e2e-setup/                    (harness)
    ├── crabbox-setup/                (harness) — isolated cloud box per agent
    └── pr/                           (harness) — verify-before-ship  (+ ship-change.js)

These skills get you the structure. If you want to learn how to actually build agents and run compounding loops for your own business, that's what I go deep on inside AI Builder Club: weekly live builder workshops, courses on production AI agents, AI coding beyond the basics, and building your first LLM apps, plus a community of people building the same way.

→ Join AI Builder Club

Built by Jason Zhou (AI Jason).