Jev Decision Layer — AI skill for Claude Code
Deterministic System One cognitive decision layer, token ROI telemetry, multi-key rotation hub, and live glassmorphic observability dashboard for AI agents (Google Antigravity, OpenAI Codex, Claude Co.
How to install Jev Decision Layer
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open mad-helpers/jev-decision-layer and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Jev Decision Layer does
Deterministic System One cognitive decision layer, token ROI telemetry, multi-key rotation hub, and live glassmorphic observability dashboard for AI agents (Google Antigravity, OpenAI Codex, Claude Code).
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README
⚡ Jev Decision Layer & Reactive Telemetry Dashboard
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**Ultra-fast deterministic System One decision gateway, token optimization engine, multi-key rotation hub, and live reactive telemetry dashboard for autonomous AI agent swarms.**
[](LICENSE) [](https://www.python.org/) []() []() []() []()
[English Documentation](#-english-overview) • [راهنمای فارسی](#-راهنمای-فارسی-مستندات-persian-guide) • [Architecture Guide](ARCHITECTURE.md) • [Live Dashboard](jev_dashboard.html)
🚀 English Overview
Autonomous agent workflows spend millions of tokens calling large foundational models ($3.00–$15.00 / 1M tokens) for bounded, categorical choices (e.g., *Which tool should I invoke?*, *Which library is best suited for 3D web rendering?*, *Should I run test A or test B?*).
**Jev Decision Layer** routes these decisions to TypeSafe Jev System One:
- ⚡ Sub-250ms Latency (p50: 210ms vs 2,500ms for large LLMs).
- 💰 **99.8%
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