> ## Documentation Index
> Fetch the complete documentation index at: https://www.opendirectory.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# meta-tribeV2-skill
> AI Skill that uses Meta's TRIBE v2 fMRI Model to analyze the neuroscience of video hooks, reels, and scripts.
**Category:** GTM Intelligence · **Version:** `1.0.0` · **Author:** `Varnan-Tech` · **Compatibility:** All targets (claude, codex, opencode, gemini, anti-gravity, openclaw, hermes)
AI Skill that uses Meta's TRIBE v2 fMRI Model to analyze the neuroscience of video hooks, reels, and scripts.
Instead of guessing what makes a hook engaging using prompt engineering, this skill predicts actual human brain activity across the scientifically validated Yeo-7 Functional Networks, giving you an evidence-based Engagement Report for your content.
***
## Install
```bash theme={null}
npx "@opendirectory.dev/skills" install meta-tribeV2-skill --target claude
```
```bash theme={null}
npx skills add Varnan-Tech/opendirectory --skill meta-tribeV2-skill
```
```bash theme={null}
/plugin marketplace add Varnan-Tech/opendirectory
/plugin install opendirectory-gtm-skills@opendirectory-marketplace
```
1. Copy `https://github.com/Varnan-Tech/opendirectory/tree/main/skills/meta-tribeV2-skill` into [download-directory.github.io](https://download-directory.github.io/) to download the ZIP.
2. Open **Claude Desktop** -> **Customize** -> **Skills** -> **+** -> **Upload a skill** and drop the folder containing `SKILL.md`.
[**Install meta-tribeV2-skill in Manus AI**](https://manus.im/import-skills?githubUrl=https%3A%2F%2Fgithub.com%2FVarnan-Tech%2Fopendirectory%2Ftree%2Fmain%2Fskills%2Fmeta-tribeV2-skill\&utm_source=opendirectory)
## What This Skill Does
This skill provides the infrastructure to host the massive 80GB TRIBE v2 model pipeline and gives your AI Agent the ability to:
1. Process video, audio, or text scripts.
2. Intercept and optimize the media (downscaling video to 360p at 10fps to avoid hour-long bottleneck processing times).
3. Process the content through V-JEPA (Vision), W2V-BERT (Acoustics), and LLaMA 3.2 3B (Linguistics).
4. Predict human brain fMRI activity across the Yeo-7 networks.
5. Generate an actionable, human-readable neuroscience report without the jargon.
***
## Deployment Options
Because TRIBE v2 requires a massive amount of VRAM (24GB for text, up to 80GB for video), we offer 3 different deployment options so anyone can use it, regardless of budget or technical expertise.
### 1. Google Colab (Zero Cost, Decoupled)
Best for users without a cloud budget. Colab provides free T4 GPUs.
* How it works: We use a decoupled architecture. You run the heavy AI inference in a Colab Notebook, which outputs a preds.npy prediction file. You then run a local script on your laptop to generate the report.
* Setup:
1. Open Google Colab and upload the script from scripts/colab\_inference.py into a new Notebook.
2. Run the notebook. It will output preds.npy and segments.json.
3. Download those files to your machine and run: `python scripts/local_analyze.py --preds preds.npy`. This will output a text report and an ASCII terminal graph showing the engagement peaks and valleys.
### 2. RunPod (Serverless, Pay-per-second)
Best for production agents and developers. You only pay for the seconds the model is running.
* How it works: We provide a RunPod Handler and a custom Dockerfile that caches the 80GB model inside the image.
* Setup:
1. Build the Docker image using server/Dockerfile.runpod: docker build -f Dockerfile.runpod -t tribe-runpod .
2. Push the image to Docker Hub or GHCR.
3. Create a new RunPod Serverless Endpoint using your image URL.
4. Point your AI Agent to your RunPod Endpoint URL.
### 3. AWS EC2 Persistent (Enterprise, BYO-Compute)
Best for heavy, continuous usage.
* How it works: Automatically provisions an AWS g5.12xlarge instance (4x A10G GPUs) and runs a FastAPI server.
* Setup:
1. Ensure your AWS account has a vCPU quota limit of at least 48 for "Running On-Demand G and VT instances".
2. Run bash scripts/launch\_persistent.sh to provision the instance.
3. Run export HF\_TOKEN="your\_token" followed by bash scripts/deploy\_to\_persistent.sh to build and launch the Docker API.
#### AWS GPU Lifecycle & Estimated Costs
Running the `g5.12xlarge` instance (4x A10G GPUs) provides incredible speed but costs **\$7.09 per hour** on On-Demand pricing. It is crucial to manage this lifecycle.
1. **Launch:** Run `bash scripts/launch_persistent.sh` (Takes \~3 minutes).
2. **Analyze:** Run your videos through the API.
3. **Terminate:** When you are completely finished for the day, you MUST terminate the instance to stop billing.
* Run `aws ec2 describe-instances --filters "Name=instance-state-name,Values=running"` to find your Instance ID.
* Run `aws ec2 terminate-instances --instance-ids `.
* *Do not just "stop" the instance if you don't want to pay for EBS Volume storage costs overnight. Terminate it.*
***
## HuggingFace Authentication (Required for all methods)
TRIBE v2 relies on meta-llama/Llama-3.2-3B, which is a Gated Model.
1. Create a HuggingFace account.
2. Go to the Llama 3.2 3B page and TRIBE v2 page and agree to Meta's license terms.
3. Generate a HuggingFace Access Token (Read permissions) at huggingface.co/settings/tokens.
4. Supply this token via the HF\_TOKEN environment variable.
***
## The Neuroscience of the Engagement Report
The AI agent will read the raw API output and translate the neuroscience into plain English for you:
* VAN (Ventral Attention Network): Translated to "Is this surprising enough to stop a scroll?". High VAN means the content is novel and creates a pattern interrupt.
* DMN (Default Mode Network): Translated to "Will people get bored and tune out?". High DMN is bad. It means the brain is wandering. The AI uses this to identify "Cut Candidates" in your video.
* DAN (Dorsal Attention Network): Translated to "Are people actively following along?". High DAN means strong logical focus.
* Limbic Network: Translated to "Does this make people feel something?". High Limbic means strong emotional response.
Check out the [Results Showcase](/docs/skills/gtm-intelligence/meta-tribeV2-skill/showcase) for actual examples of Neuro-Marketing reports generated by this skill.
This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.