u/SoundDr Thank you for everything you do for the AGY Community. We really appreciate all your hard work! Please keep up the Googler awesomeness!!!!

https://preview.redd.it/drungao0oagh1.png?width=588&format=png&auto=webp&s=416679522266ef6e4b24b5bb6e7b7470d07389ff

AGY Builders :

If you are working with Google's open Gemma model family or building custom agent workflows around them, this tool simplifies standardizing local agent capabilities.

Check out the official community repo: gemma-skills

👉 GitHub Repo:https://github.com/google-gemma/gemma-skills

💡 What is it?

gemma-skills provides modular skill capabilities designed specifically for model and agent interactions within the Gemma ecosystem. Instead of writing custom setup glue code for every project, you can plug in dedicated skills directly into your CLI environment or agent framework.

📦 Key Skills Included

• gemma-dev: Purpose-built skill for developing applications with Gemma models or handling general architectural and technical inquiries about the Gemma family.
• gemma-trainer: Specialized skill for training, fine-tuning, and adapting Gemma models (supporting SFT, DPO, RLHF, and Reward Modeling) on local hardware.

🛠️ Quick Installation

You can easily install skills globally or into your current workspace using either npx skills or ctx7:

Bash

# Using Vercel skills CLI
npx skills add google-gemma/gemma-skills --skill gemma-dev --global

# Using Context7 skills CLI
npx ctx7 skills install /google-gemma/gemma-skills gemma-dev

Check out the repository link for setup steps, usage patterns, and contribution guidelines:

https://github.com/google-gemma/gemma-skills

The NotebookLM Antigravity Skill is designed to expand how you interact with NotebookLM by introducing streamlined workflows and enhanced prompting frameworks to get around common friction points (lifting the "gravity" holding your notebook interactions back).

🚀 Key Features & Capabilities

• Enhanced Knowledge Synthesis: Automates and structures complex multi-document analysis.
• Custom Output Formatting: Easily pivot your research into clean Markdown, structured summaries, actionable task lists, or educational guides.
• Seamless Integration: Designed to plug directly into your agentic/AI skill workflows.

🛠️ How to use it

Check out the step-by-step instructions and installation guide directly on the GitHub repository: [https://github.com/JunSuzuki1973/notebooklm-antigravity-skill](https://github.com/JunSuzuki1973/notebooklm-antigravity-skill)

Good day everyone! I'm a software developer with 2 years experience before the AI and I have a solid understanding building software manually. However, I want to know what's the difference using skills.md than just prompting in antigravity ide like I used to do recently. Is there merit or it's just for token maxing?

Added a /effort command & new model Gemini 3.6 Flash

https://preview.redd.it/q5ud9rj8cneh1.png?width=2238&format=png&auto=webp&s=0f19b1080786a71857061f56c35b5313e7a36fb5

I worked half the day with it:

1. its even faster than gemini flash 3.5 like making plans and finished in less than 2 mins thats just crazy (opus takes the same only analyzing my prompt)
2. it does less loops and takes less tokens to finish my tasks
3. it actually does not feel the dumbest model ever like flash 3.5.
4. Less halucinations.

Is definitly good enough for being my daily driver from now on

Unfortunate even after taking less tokens and 20% cheaper, google still having the worst qu0ta yet in the market lol.

AGY Builders,

We are all trying to build useful and scalable workflows for our AGY CLI and ecosystem, but the speed at which we need to learn, build, and deploy new things is incredibly overwhelming. If you are feeling that pressure, you are in the right place here at r/GoogleAntigravityCLI.

Over the past few weeks, I have been testing an "AGY WIKI OKF" setup that I put together myself (after inviting some members of this community to collaborate; mod is not proud). I know some folks might hesitate to trust a tutorial from a random Redditor, but I wanted to share this with the community anyway because it actually works.

I was able to build this because I am all-in on Google and the Antigravity Ecosystem. I’m a truly AGY—I am not some ultra-smart, 10x developer, but I know how to work hard, I dig for the right information, and I iterate.

AGY WIKI OKF | The Idea

To build a frictionless, token-efficient knowledge WIKI engine that transforms static documentation or notes (information) into an active, intelligent collaborator—orchestrated entirely by Antigravity CLI.

The core philosophy is simple: treat knowledge management as a clean pipeline and tokens as a premium, finite resource.

By anchoring this architecture to Google’s Antigravity CLI, the AGY WIKI OKF bypasses heavy middleware and complex UI layers, delivering a hyper-focused AI partner built entirely for execution speed, context hygiene, and minimal footprint.

Why adopting AGY WIKI OKF matters:

• Stay organized (AGY OCD): Structured Markdown and YAML keep the chaos in check.
• Save tokens: Doing more with less context window bloat.
• Scale shareable knowledge: Making it easy to pass context and logic between different LLMs.
• Humans and Agents working together: One standardized, readable format that works perfectly for both of us.
• BYOD (Bring Your Own Data): Own your context. Port it to the newest model, platform, or OS instantly.

The Tools

• Antigravity CLI
• Obsidian: The IDE for the Knowledge bank
• Obsidian Web Clipper:
  • Official Site
  • Chrome Web Store
  • Firefox Add-on

The WIKI

In the agent-first era, a WIKI is no longer just a static graveyard for human notes; it is the operational hard drive for your agents. By maintaining a highly structured WIKI, you ensure that every piece of context is stored in a clean, machine-readable format. This means that whether you are testing a new modular skill or spinning up a specialized agent, your AGY CLI knows exactly where to find the precise context it needs to generate autonomous action, moving you far beyond simple, reactive conversational text.

Reference: Gist on Knowledge Representation

Google Open Knowledge Format (OKF)

Google’s Open Knowledge Format (OKF) feels like the exact missing piece we've needed for orchestrating multiple AI agents effectively. It provides a vendor-neutral, interoperable standard for storing and sharing organizational knowledge.

Why this is huge for orchestration:

1. The "Lingua Franca" for Agents: Any agent can read it out of the box without platform-specific integrations.
2. Seamless Context Passing: Specialized agents can access, update, and pass the exact same foundational context back and forth.
3. Human-in-the-Loop Oversight: Because OKF is just Markdown and YAML, it’s inherently readable and auditable.
4. Scalable Knowledge: It acts as a shared, living library that grows alongside your agents.

AGY WIKI OKF Integration

Structuring an AGY Wiki using OKF revolutionizes how complex knowledge is shared. By standardizing documentation with concise Markdown and YAML frontmatter, OKF provides a unified taxonomy for cataloging AGY CLI slash commands, SKILLS.md behaviors, and Agent-to-Agent (A2A) workflows or context in general

. It is highly token-efficient, stripping away bloated formatting and maximizing context window limits.

The Prompt for Building an AGY WIKI OKF

AGY CLI WIKI OKF PROMT EXAMPLE

/grillme I want to initialize a brand-new, empty Obsidian vault from scratch that adheres strictly to the Open Knowledge Format (OKF) standard, with the specific intent of potentially open-sourcing or sharing this architecture later. I want a purely blank, skeletal framework with no pre-populated data. Please grill me to define the optimal architectural blueprint for this vault. I need you to interrogate me on: Do not generate the directory structure or files until you are satisfied that you have captured all my requirements for a production-ready, shareable knowledge base. 
Core Directory Hierarchy: How should we structure the root (e.g., /concepts, /resources, /indices, /log) to be intuitive for external users? Template Strategy: What base boilerplate templates do we need to ensure every new file is automatically OKF-compliant and structured for consistent metadata? Workflow Logic: Since this is a fresh start, what processes should we bake in for capturing information vs. refining knowledge that could be easily documented for others? CLI Integration: What specific file locations or configurations do we need to ensure this vault plays nicely with the Antigravity CLI from day one? Open-Source & Contributor Documentation: What files should we create to make this a "deployable" standard? Please include requirements for: A README.md with installation and usage instructions. A CONTRIBUTING.md that defines how to add new concepts or schemas. A "System Architecture" document that explains the logic behind the folder structure and metadata fields, ensuring anyone who clones this vault understands how to extend it.

The Final File Structure

AGY WIKI OKF
    ├── .agyrc
    ├── ARCHITECTURE.md
    ├── CONTRIBUTING.md
    ├── README.md
    ├── .agy
    │   └── .keep
    ├── .obsidian
    │   ├── app.json
    │   ├── appearance.json
    │   ├── core-plugins.json
    │   └── workspace.json
    ├── 00-Inbox
    │   └── .keep
    ├── 10-Projects
    │   └── .keep
    ├── 20-Areas
    │   └── .keep
    ├── 30-Resources
    │   ├── .keep
    │   └── Google Antigravity Documentation.md
    ├── 40-Archive
    │   └── .keep
    ├── 99-Meta
    │   └── Templates
    │       ├── Base_Template.md
    │       ├── Project_Template.md
    │       └── Resource_Template.md
    └── Clippings

AGY CLI WIKI OKF PARA FILE STRUCTURE

Obsidian screenshot using OKF for knowledge context in Antigravity CLI

TL;DR

• AGY WIKI OKF: Organizes your information (context) , AGY CLI commands, SKILLS.md behaviors, and A2A workflows into a token-efficient, shareable format that reduces inference costs for any LLM.
• Open Knowledge Format (OKF): Provides a standardized, vendor-neutral way to share context (Markdown + YAML), preventing platform lock-in and eliminating data fragmentation.

AGY Builders, I genuinely want your input on this. Please comment, grill me, roast me, ask questions, or give me your raw feedback on this AGY WIKI OKF setup. We are building the foundation to organize and share our data in the BYOD era. Let's build the future together.