# Antigravity Workflows

> Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA. Use when this capability is needed.

- Skill: `tomevault-io/antigravity-workflows` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/antigravity-workflows`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/antigravity-workflows/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/antigravity-workflows

---


# Antigravity Workflows

Use this skill to turn a complex objective into a guided sequence of skill invocations.

## When to Use This Skill

Use this skill when:
- The user wants to combine several skills without manually selecting each one.
- The goal is multi-phase (for example: plan, build, test, ship).
- The user asks for best-practice execution for common scenarios like:
  - Shipping a SaaS MVP
  - Running a web security audit
  - Building an AI agent system
  - Implementing browser automation and E2E QA

## Workflow Source of Truth

Read workflows in this order:
1. `docs/WORKFLOWS.md` for human-readable playbooks.
2. `data/workflows.json` for machine-readable workflow metadata.

## How to Run This Skill

1. Identify the user's concrete outcome.
2. Propose the 1-2 best matching workflows.
3. Ask the user to choose one.
4. Execute step-by-step:
   - Announce current step and expected artifact.
   - Invoke recommended skills for that step.
   - Verify completion criteria before moving to next step.
5. At the end, provide:
   - Completed artifacts
   - Validation evidence
   - Remaining risks and next actions

## Default Workflow Routing

- Product delivery request -> `ship-saas-mvp`
- Security review request -> `security-audit-web-app`
- Agent/LLM product request -> `build-ai-agent-system`
- E2E/browser testing request -> `qa-browser-automation`
- Domain-driven design request -> `design-ddd-core-domain`

## Copy-Paste Prompts

```text
Use @antigravity-workflows to run the "Ship a SaaS MVP" workflow for my project idea.
```

```text
Use @antigravity-workflows and execute a full "Security Audit for a Web App" workflow.
```

```text
Use @antigravity-workflows to guide me through "Build an AI Agent System" with checkpoints.
```

```text
Use @antigravity-workflows to execute the "QA and Browser Automation" workflow and stabilize flaky tests.
```

```text
Use @antigravity-workflows to execute the "Design a DDD Core Domain" workflow for my new service.
```

## Limitations

- This skill orchestrates; it does not replace specialized skills.
- It depends on the local availability of referenced skills.
- It does not guarantee success without environment access, credentials, or required infrastructure.
- For stack-specific browser automation in Go, `go-playwright` may require the corresponding skill to be present in your local skills repository.

## Related Skills

- `concise-planning`
- `brainstorming`
- `workflow-automation`
- `verification-before-completion`

---

<!-- AGI-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

```bash
# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Antigravity Workflows"
```

### Storing Results

After completing work, store workflow/automation decisions for future sessions:

```bash
python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags antigravity-workflows workflow
```

### Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>
```

### Playbook Engine

Combine this skill with others using the Playbook Engine (`execution/workflow_engine.py`) for guided multi-step automation with progress tracking.

<!-- AGI-INTEGRATION-END -->

---
> Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.
<!-- tomevault:4.0:skill_md:2026-04-13 -->