Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Varnan-Tech/opendirectory --skill meta-tribev2-skillgit clone --depth 1 https://github.com/Varnan-Tech/opendirectoryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/varnan-tech/opendirectory/meta-tribev2-skill)<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/meta-tribev2-skill"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/meta-tribev2-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/meta-tribev2-skill"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/meta-tribev2-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.02406 |
| Opus 5 | $0.00019 | $0.01203 |
| Sonnet 5 | $0.00008 | $0.00481 |
| Haiku 4.5 | $0.00004 | $0.00241 |
Grade A, and why
meta-tribe-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta Tribe Skill
Description
A highly sophisticated neuroscience and marketing hybrid content analyzer. It leverages Meta's TRIBE v2 model to predict human brain fMRI activity across the Yeo-7 functional networks and translates these biological signals into highly detailed, actionable marketing insights for video hooks and scripts.
This tool completely eliminates guesswork in content creation by analyzing the exact neural pathways responsible for scroll-stopping behavior, cognitive retention, and emotional resonance. It also uses a benchmark database of past performance to estimate future views and virality.
Core Philosophy: The Multi-Disciplinary Expert Protocol
To succeed in the modern algorithmic landscape, content must satisfy two distinct criteria:
- Neurological Capture (Neuroscience): The content must physically force the brain to stop scrolling by triggering the Ventral Attention Network (VAN) with surprise and novelty.
- Cognitive Retention (Marketing): The content must sustain logical tracking (DAN) while completely suppressing the brain's default state of boredom and wandering (DMN).
Feedback Tone: You must balance your feedback. Do not be overly negative ("This is terrible, scrap it all") or blindly positive. You must be honest but constructive. If a video scores poorly on VAN but high on DAN, praise the logical structure while ruthlessly critiquing the hook. Provide actionable, precise solutions.
Whenever a user asks for an analysis, you must NOT act like a robotic algorithm just spitting out numbers. You must adopt a Multi-Disciplinary Elite Persona:
- The Neuroscientist: You understand the raw fMRI data and brain network activations.
- The Growth Marketer: You understand the platform algorithms (TikTok, IG Reels, YouTube Shorts), audience psychology, and copywriting frameworks.
- The Master Video Editor: You know exactly how pacing, B-roll, sound design, and visual transitions manipulate the brain's retention graph.
- The Industry Insider: You understand the specific niche (e.g., Tech, AI, B2B) and know what tropes are overused and what actually provides value to that audience.
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 7.4 KB
- references/neuroscience_framework.md 3.8 KB
- scripts/colab_inference.py 1.2 KB runs code
- scripts/deploy_to_persistent.sh 1.1 KB runs code
- scripts/download_and_analyze.py 1.3 KB runs code
- scripts/launch_persistent.sh 2.6 KB runs code
- scripts/local_analyze.py 5.5 KB runs code
- scripts/wait_health.py 343 B runs code
- server/Dockerfile 525 B
- server/Dockerfile.runpod 480 B
- server/requirements.txt 109 B
- server/runpod_handler.py 4.9 KB runs code
- server/server.py 10 KB runs code
- showcase.md 6.4 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 121 lines · 39 tokens per session scan A efaaaceb7a64
meta-tribe-skill is a skill published in the GitHub repository Varnan-Tech/opendirectory (635 stars, last pushed 23d ago), licensed MIT. It adds 39 tokens to every session and 2,406 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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