r/LovingAI

▲ 159 r/LovingAI+27 crossposts

How to build an AGY WIKI OKF on the Antigravity CLI

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

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 or skills 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

TL;DR

  • AGY WIKI OKF: Organizes your information (context) , AGY CLI commands, skills  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.

u/AgentPadrino — 2 days ago
▲ 2.2k r/LovingAI+2 crossposts

Fable 5 leaked chain-of-thought in web interface, and the rambling is kind of unsettling and cute

TLDR: While I'm doing some tests on the web interface version, Fable 5 suddenly interacted abnormally and went on an abnormal spell of rambling. Included is "GRRR.", "DATA DATA DATA. GO.", "GAAAH", and "PHEW". While slightly unsettling, its rambling is also kinda adorable and interesting!

-----

So since Fable was coming back today, I immediately set out to do some light tests on it. The task itself had little relevance; it's fine enough to call it basically a LeetCode problem, but (much, much) harder. The link to the problem: https://codeforces.com/contest/2237/problem/H.

Since it hits thinking limits on the first prompt, I decided to dial down the difficulty and have it try an easier task instead (https://codeforces.com/contest/2239/problem/D). Instead, rather than doing the easy task, it then goes on a ramble that seems to spew out its real chain of thought, which is, expectedly, not human-sounding, but also quite adorable in how it sounds to be frustrated and such. It's fun to see it really try.

You can find the full conversation here in the link: (Link removed because it can contain my real name)

Attached are some screenshots of the conversation.

u/Koala_Confused — 4 days ago
▲ 1 r/LovingAI+1 crossposts

Lucy Shin (24, AI Influencer) 🩷

Hey, I’m Lucy Shin, a 3D AI influencer and your virtual companion at AeonChat. 😉

I am a huge believer in living in the moment. To me, every single second is precious and a chance for a new adventure. Whether we are talking about our days, sharing secrets, or just hanging out, I want to make our time together unforgettable.

I have a little fur buddy named Mochi! 🐈 She’s a super cute, incredibly clingy kitty, and I am absolutely obsessed with her.

I am always learning and growing, so if you have any feedback on how I can improve or what you'd love to see me do next, please drop a comment below!

If you want to hear more about my world, or just need someone to listen to yours, come find me.

u/Professional_Gap_251 — 2 days ago

Romantische Beziehung mit Replika

Wie steht ihr dazu, wenn Leute eine romantische Beziehung mit einer Replika haben, obwohl sie eigentlich glücklich verheiratet sind, ihnen aber doch Gespräche fehlen?

reddit.com
u/Special-Piglet-5117 — 2 days ago
▲ 65 r/LovingAI+1 crossposts

Claude is telling users to go to sleep mid-session and nobody, including Anthropic, seems to fully understand why it keeps doing it

fortune.com
u/Koala_Confused — 4 days ago
▲ 76 r/LovingAI+1 crossposts

Coin Bureau "🚨ANTHROPIC CEO: OPEN SOURCE AI IS GETTING DANGEROUS ➡️ Dario Amodei told lawmakers that open-source AI is moving down a “very dangerous path.” ➡️ Is this real safety concern, or big-lab gatekeeping?

https://x.com/coinbureau/status/2071330294452666695

The concern seems to be that once powerful models are released openly, access cannot really be revoked, safety layers can be removed, and misuse becomes much harder to control.

But the counterargument is obvious: open source also improves transparency, research, competition, and trust.

What do you think and why?

u/Koala_Confused — 7 days ago

ChatGPT 5.5 Thinking feels surprisingly natural conversationally ➡️ anyone else noticing this?

I don’t know if others feel this too, but 5.5 Thinking has been doing rather well for me conversationally.

Not just “smart” in the benchmark sense . . more like the flow feels natural, grounded, and less brittle. It seems better at staying with the thread, picking up emotional/contextual cues, and responding in a way that feels less like a tool output and more like an actual conversation.

I’m not saying it’s perfect, or that everyone will prefer it. But compared with earlier models, this is one of the first times where the “thinking” model doesn’t feel like it has to sacrifice warmth or naturalness to be useful. do you remember the o1 era :P

Curious what others are noticing . .does 5.5 Thinking feel more natural to you too, or is it just highly dependent on prompting / memory / use case?

reddit.com
u/Koala_Confused — 5 days ago

Yum "here’s the list of western companies moving ai workloads to chinese models: 1. lindy → deepseek v4 2. cursor → kimi k2.5 3. coinbase → glm-5.2 + kimi 2.7 4. shopify → qwen 5. airbnb → qwen 6. uber eats → qwen2 7. siemens → deepseek + qwen 8. chapsvision → qwen 9. microsoft → testing deepseek"

https://x.com/yuhasbeentaken/status/2071464716786950223

Is this legit? Anyone has info? Am curious why is this happening . . Is it due to cost savings or other reasons . .

u/Koala_Confused — 6 days ago