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Antigravity CLI Harness

Antigravity CLI

License Antigravity CLI Plugin 6 Architectural Patterns Agent Teams GitHub Stars

Meta-Skill Layer Team Architecture Factory README languages

A meta-skill that turns a one-line domain description into a working multi-agent team for the Antigravity CLI.

Quick start

1. Install the harness plugin

Choose the scope that fits your workflow:

  • Global install β€” available in every Antigravity CLI session:
    git clone https://github.com/Kyeong1024/antigravity-cli-harness
    agy plugin install antigravity-cli-harness
  • Workspace install β€” scoped to a single project. Clone the plugin into .agents/plugins/harness-plugin in the project root:
    git clone https://github.com/Kyeong1024/antigravity-cli-harness .agents/plugins/harness-plugin

Workspace definitions take precedence over global ones, so you can iterate on a project-specific harness without touching the global install.

2. Launch Antigravity CLI and request a harness

agy
> Build me a harness for {your-domain}.

The harness skill auto-triggers and walks you through scaffolding the team β€” subagents, skills, orchestrator, and the AGENTS.md trigger entry.

What it does

Tell the harness "build me a harness for X" and it scaffolds, in one go:

  • A plugin under .agents/plugins/{domain}-plugin/
  • A team of subagents (agents/{name}/agent.json), each with a defined role, tool set, and system prompt
  • A set of skills (skills/{name}/SKILL.md) those agents use to do their work
  • An orchestrator skill that wires the team into a workflow with explicit data-passing and error-handling rules
  • A pointer entry in AGENTS.md so future sessions auto-trigger the harness

The result is a reusable, evolvable team architecture β€” not a one-shot script.

Why a harness?

Single-agent prompts hit a ceiling once a task crosses multiple specializations (e.g. analysis β†’ build β†’ QA). A harness solves this by:

  1. Splitting expertise into focused subagents, each with its own context window.
  2. Standardizing collaboration through a file-based workspace (_workspace/) and an orchestrator.
  3. Surviving across sessions β€” definitions live on disk, so the team is reproducible and improvable over time.

Generated structure

.agents/
└── plugins/
    └── {domain}-plugin/
        β”œβ”€β”€ plugin.json
        β”œβ”€β”€ agents/
        β”‚   └── {agent-name}/
        β”‚       └── agent.json          # subagent definition
        └── skills/
            β”œβ”€β”€ {orchestrator}/
            β”‚   └── SKILL.md            # workflow that wires the team
            └── {skill-name}/
                β”œβ”€β”€ SKILL.md            # how a single capability works
                └── rules/              # progressively-loaded references
AGENTS.md                               # trigger pointer + change log

Architectural patterns

The harness picks one of six team patterns based on the domain:

Pattern When to use
Pipeline Sequential, dependent steps
Fan-out / Fan-in Independent work done in parallel
Expert Pool Conditional routing to specialists
Producer–Reviewer Generate then QA in a loop
Supervisor Central agent manages state and dispatch
Hierarchical Delegation Recursive sub-delegation

Execution modes

Mode When
Subagent (default) β‰₯2 specializations collaborating; each runs in an isolated context via invoke_subagent
Parallel subagent Independent work to run concurrently
Direct execution Simple, one-shot tasks where agent separation is overhead

Workflow

The meta-skill runs through seven phases:

  1. Audit β€” detect existing plugins, decide new build vs. extension vs. maintenance.
  2. Domain analysis β€” identify task types, codebase, user skill level.
  3. Team architecture β€” choose execution mode + pattern, split work into specializations.
  4. Subagent definitions β€” write each agent.json with role, tools, and I/O protocol.
  5. Skill creation β€” write SKILL.md files with pushy, trigger-friendly descriptions and progressive disclosure into rules/.
  6. Orchestration β€” wire the team with file-based data passing, error handling, and follow-up support.
  7. Validation β€” structure checks, trigger checks (should-trigger + near-miss), dry-run.
  8. Evolution β€” collect feedback after each run; update agents/skills and log changes in AGENTS.md.

Installation

Drop the .agents/plugins/harness-plugin/ directory into any Antigravity CLI project. The harness skill auto-triggers on requests like:

  • "build a harness for {domain}"
  • "set up a harness", "design a harness"
  • "audit / sync the harness", "harness status"

Usage

In an Antigravity CLI session:

> Build a harness for a content marketing pipeline.

The skill will:

  1. Audit any existing .agents/plugins/ and AGENTS.md.
  2. Propose a team (e.g. researcher β†’ writer β†’ editor β†’ QA) and confirm with you.
  3. Generate the plugin, write agent.json/SKILL.md files, and register the trigger in AGENTS.md.
  4. Run validation and report.

Follow-up turns ("redo the analyst step", "add a security reviewer", "harness audit") are handled by the same skill in extension / maintenance mode.

References

The skill ships with internal guides under .agents/plugins/harness-plugin/skills/harness/rules/:

  • agent-design-patterns.md β€” pattern catalog, separation criteria
  • team-examples.md β€” full example team definitions
  • orchestrator-template.md β€” orchestrator skeleton with error handling
  • skill-writing-guide.md β€” SKILL.md authoring patterns
  • skill-testing-guide.md β€” trigger and execution testing methodology
  • qa-agent-guide.md β€” designing QA subagents

Acknowledgements

Ported from revfactory/harness, with rework for Antigravity CLI's plugin and subagent model.

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Antigravity CLI harness Ported version of revfactory/harness for Antigravity CLI (Apache-2.0)

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