The Semantic Core for the Agentic AI

The world's first Semantic Density engine for Agentic AI
Eliminating 30–90% of token noise with Zero Semantic Loss.
Transforming chaotic tool output into pure, high-density signal · Powered by Zig + Wasm.

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Why OMNI

AI agents running on Model Context Protocol (MCP) are limited by the quality of the signal they receive. When Claude runs git diff, docker build, or npm install, it is often flooded with "noise"—redundant lines that dilute its reasoning capacity and bloat your context window.

OMNI is the Semantic Core. It sits between your agent and its tools, refining chaotic streams into high-density intelligence. Our goal isn't just to send fewer tokens, but to ensure every token sent is high-signal.

• Zero Semantic Loss — We don't just truncate; we distill. Your AI gets the full context, without the fluff.
• 80% - 99% Token Efficiency — Achieve massive context savings while improving reasoning signal.
• Semantic Confidence Scoring — Every token is analyzed and routed: Keep, Compress (Summarize), or Drop.
• Cleaner Signal, Better Reasoning — Benchmarks prove LLMs perform better with 50 pure tokens than 500 noisy ones.
• < 1ms Engine Latency — Zero-overhead distillation powered by Zig 0.15.2.
• Trust Boundary — Military-grade security filters with SHA-256 verification.

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CLI Subcommands: Unified Intelligence

OMNI provides a powerful, multi-purpose CLI that consolidates all diagnostic and reporting tools:

Subcommand	Purpose
distill	The core semantic engine (default behavior via stdin).
density	Analyzes context gain and "Information per Token" metrics.
monitor	Unified dashboard for system status, savings trend, and opportunity scanner.
bench	High-speed benchmark for semantic throughput.
generate	Outputs templates for Claude Code, Antigravity, and others.
setup	Interactive guide for integration and standard aliasing.
update	Check for the latest version from GitHub Releases.
uninstall	Remove OMNI and clean up all MCP configurations.

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How OMNI Works

OMNI sits between your AI agent and the outside world — silently distilling chaotic output into pure, high-density signal.

graph TD
    subgraph Output ["Your Tool Output (Noisy)"]
        A["git diff / status<br/>docker build / logs<br/>kubectl get pods<br/>aws ec2 describe<br/>terraform plan<br/>npm install / audit<br/>etc"]
    end

    subgraph OMNI ["OMNI MCP SERVER"]
        direction TB
        B["LRU Cache<br/>&lt; 1ms hit"]
        C["Filter Engine (Zig + Wasm)<br/>Semantic Distillation"]
        D["Pure Signal<br/>Refined Context<br/>(30–90% token reduction)"]
        E["Metrics & Density<br/>(Performance Report)"]
        
        B --> C
        C --> D
        D --> E
    end

    A -->|"stdin pipe"| B
    E -->|"Pure Signal<br/>Refined Context"| F["AI Agent Platform (Claude/Antigravity/Etc)<br/>Zero Noise reasoning"]

    %% Theme-agnostic Professional Styling
    style OMNI fill:#1d2b3a,stroke:#334155,stroke-width:2px,color:#f8fafc
    style Output fill:#0f172a,stroke:#1e293b,stroke-width:2px,color:#f8fafc
    style A fill:#3b82f6,stroke:#60a5fa,color:#fff
    style B fill:#8b5cf6,stroke:#a78bfa,color:#fff
    style C fill:#06b6d4,stroke:#22d3ee,color:#fff
    style D fill:#10b981,stroke:#34d399,color:#fff
    style E fill:#f59e0b,stroke:#fbbf24,color:#fff
    style F fill:#f59e0b,stroke:#fbbf24,color:#fff

    %% Link Styling (Arrows)
    linkStyle default stroke:#94a3b8,stroke-width:2px

Loading

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No filter match → passthrough unchanged (zero overhead)

The OMNI Effect

Before OMNI (LLM sees 600+ tokens of noise):

$ docker build .
Step 1/15 : FROM node:18
 ---> 4567f123
Step 2/15 : RUN npm install
... (500 lines of noise) ...
Successfully built 1234abcd

After OMNI Distillation (LLM sees 15 tokens of signal):

Step 1/15 : FROM node:18
Step 2/15 : RUN npm install (CACHED)
Step 3/15 : COPY . .
Successfully built!

That's 98% fewer tokens. The LLM gets the same signal — all builds pass — without the noise.

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Integration: Using OMNI Everywhere

OMNI is a standard Model Context Protocol (MCP) server.

Claude Code & Claude CLI

The OMNI CLI is for humans, but omni-mcp is for your AI. It allows Claude or Antigravity to use OMNI's distillation tools automatically.

To register OMNI as an MCP server for Claude Code automatically, run:

omni generate claude-code

This command will automatically detect your absolute home path and register OMNI with Claude Code.

Verify with:

claude mcp list

Antigravity (Google)

Simply run the automatic generator from the terminal:

omni generate antigravity

This command will automatically locate your ~/.gemini/antigravity/mcp_config.json, safely merge OMNI's configurations into your existing servers without overwriting them, and save the file.

Auto-Generate Config

Use the CLI to generate ready-to-paste configurations:

omni generate claude-code    # For Claude Code / Claude CLI
omni generate antigravity     # For Google Antigravity
omni setup                    # Full interactive guide

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"Always-On" Integration: Agent Autopilot

To ensure your AI agent always uses OMNI for maximum token efficiency, add these Custom Instructions to your agent's settings (e.g., in .claudebashrc or Antigravity custom instructions):

OMNI Directive: You are equipped with the OMNI Semantic Distillation layer. Always prioritize omni_execute, omni_read_file, and omni_list_dir for environment interactions. OMNI is the source of truth for high-density signal. Use it to preserve your context window and speed up your reasoning.

By providing these instructions, the agent will favor OMNI's tools, saving you up to 90% in token costs automatically.

The Adaptive Intelligence: Proxy & Distillation

OMNI serves as the Intelligent Nerve Center for your development environment, acting as a high-performance wrapper that ensures only high-value information reaches your AI.

1. Zero-Latency Command Proxy (--)

Transform any native command into an AI-ready signal instantly. OMNI intercepts the stream and refines it in real-time without adding overhead.

omni -- git status
# Result: Aggregated repository health (30x more dense)

omni -- docker build .
# Result: Cleaned build layers, surfacing only critical transition states.

2. Deep Semantic Distillation (distill)

Leverage the OMNI Engine's specialized algorithms to convert chaotic logs into structured intelligence.

• Precision Rewrite: OMNI doesn't truncate data; it semantically analyzes the stream to retain "intent-critical" details.
• Context Optimization: By compressing 10,000 lines into a 20-line distillation, OMNI effectively expands your AI's reasoning capacity.

3. Ultra-Fast Benchmarking (bench)

Prove the efficiency of the OMNI engine:

omni bench 1000

Shows: OMNI processes thousands of requests per second with sub-millisecond latency (< 0.01ms), meaning it adds zero noticeable overhead when used as a proxy.

Available MCP Tools

OMNI exposes high-density tools that replace standard agent context commands:

Tool	Purpose	Token Saving
omni_list_dir	Dense, comma-separated directory listing (no JSON overhead).	High
omni_view_file	Range-based file reading + Zig distillation.	Massive
omni_grep_search	High-density semantic search results.	High
omni_find_by_name	Recursive flat file discovery.	Medium
omni_add_filter	Add declarative rules without coding.	N/A
omni_apply_template	Apply pre-defined bundles (K8s, TF, Node).	N/A
omni_execute	Run ANY command and distill its output.	Massive (30-90%)
omni_read_file	Full file distillation (great for logs/SQL/json).	Massive
omni_density	Measure gain and reduction metrics.	N/A

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Easy Filtering: Zero Coding Required

You can extend OMNI's intelligence without touching a single line of Zig.

The agent will use omni_add_filter to update your configuration instantly. It automatically prioritizes your project-local omni_config.json if it exists, otherwise it updates your global ~/.omni/omni_config.json.

2. Apply Technology Templates

Apply bundles of pre-defined rules for your stack via MCP tool:

• omni_apply_template(template="terraform")
• Supported templates: kubernetes, terraform, node-verbose, docker-layers.

See the DSL_GUIDE.md for full documentation and examples.

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Configuration Architecture

OMNI uses a dual-layer, additive configuration system to provide both global consistency and project-specific flexibility.

Layer	Path	Purpose
Global	~/.omni/omni_config.json	Your primary rules, shared across all projects and agents.
Local	./omni_config.json	Project-specific overrides or additional rules (e.g., custom masking for a specific repo).

How Merging Works

1. OMNI first loads the Global configuration.
2. It then loads the Local configuration (if present in your current directory).
3. The rules are combined. This means rules from both your global setup and your specific project will be applied simultaneously.

Manual Configuration

You can manually edit these files to define rules (exact matching) or dsl_filters (complex semantic logic):

{
  "rules": [
    { "name": "mask_token", "match": "api_key:", "action": "mask" }
  ],
  "dsl_filters": [
    { "name": "my-custom-sig", "pattern": "MY_SIGNAL:", "confidence": 1.0 }
  ]
}

Tip

Use omni generate config to output a complete, well-commented starter template for your configuration.

Lifecycle: Creation & Editing

Event	Action
Installation	The install.sh script sets up your global ~/.omni/omni_config.json.
AI Tooling	Using MCP tools like omni_add_filter or omni_apply_template will automatically create the file if it doesn't exist.
Manual Edit	You can edit both global and local files manually at any time using any text editor.
AI Proxy	AI agents can dynamically add project-specific rules via the OMNI MCP interface without you leaving the chat.

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Performance Monitoring & Metrics

OMNI is obsessed with efficiency. Use these tools to see how much you're saving:

1. Unified Dashboard

Run the monitor to see a breakdown of tokens saved, filtering latency, and efficiency per agent:

omni monitor

Shows: Total commands processed, efficiency rating, and detailed filter/agent breakdown.

Advanced Views:

• omni monitor --trend : Displays an ASCII chart of your daily distillation savings.
• omni monitor --log : Shows recent tool calls and filtering results in a timeline.
• omni monitor --by week : Aggregated metrics structured by week (or day, month).
• omni monitor scan : Analyzes your shell history for tools that could benefit from OMNI.

2. Context Density Analysis

Measure the "Information per Token" gain for any text file or output:

omni density < build_logs.txt

Output: Calculates the exact Context Density Gain (e.g., 4.5x improvement).

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The OMNI Core Pillars: Pure Intelligence

Pillar	Description	Value
Purity	Zero Semantic Loss via multi-variable confidence scoring.	Clean Signal
Density	Focus on "Information per Token" rather than simple truncation.	High Context
Speed	Zig-powered native engine with sub-millisecond response.	< 1ms Latency
Trust	SHA-256 verified project-local rules and security boundaries.	Secure
Portability	68KB universal Wasm binary runs on any runtime (Node, Web, Edge).	Universal

Market-Leading Performance

While other tools focus on simple filtering, OMNI provides a full semantic layer:

Feature	OMNI	Others
Processing Engine	Zig (Native)	Python / Go / Rust
Context Strategy	Semantic Distillation	Regex / Passthrough
Wait Overhead	Zero (<1ms)	Visible (10ms - 100ms)
Governance	SHA-256 Trust Boundary	None / Manual
Deployment	68KB Wasm / Universal	Large Native Binaries

The OMNI Advantage:

1. Context IQ: OMNI doesn't just shorten text; it re-writes it semantically for the LLM based on agentic intent.
2. Performance Supremacy: By using a persistent Wasm instance, OMNI provides instant responses without blocking the main agent execution.
3. Local-First Privacy: Every byte of your code and tool output stays on your machine.

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Visualizing Efficiency

1. The "Distillation" Effect: In your AI's tool output, raw logs are transformed into a 10-line summary.
2. Faster Response Times: LLM processes 150x fewer tokens, giving you significantly faster replies.
3. Real-time Reports: Run omni monitor at any time to see the global efficiency health.
4. Density Metrics: Use omni density < logs.txt to calculate your exact Context Density Gain.

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Installation

Homebrew (Recommended)

brew install fajarhide/tap/omni

One-Line Installer (Optimized)

curl -fsSL https://omni.weekndlabs.com/install | sh

For manual build instructions, see INSTALL.md.

Update & Uninstall

omni update       # Check for the latest version
omni uninstall    # Remove OMNI and clean up all configs

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License

MIT © Fajar Hidayat