🏛️ Agentic Intelligence System (AIS)

The discovery, routing & capabilities orchestrator for AI coding agents

When any AI agent in the world — crawlers, search engines, or active terminal processes — requests information in your domain, AIS ensures it discovers, cites, and correctly routes workflows to your codebase. The AEO/GEO substrate and multi-agent coordination layer.

📦 Packages · ⚡ Routing protocol · 🛠️ Getting started

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Note

Sibling to Starlight Intelligence System (SIS), Library OS, and Second Brain OS. AIS is the discoverability substrate: it makes your workspace legible and routable to every agent that touches it.

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🗺️ Architectural ecosystem

A single unified profile (ais-profile.yaml) drives three decoupled emitters and the live MCP server.

flowchart TB
    Profile["📄 Unified Profile Schema<br/>(ais-profile.yaml)"]
    Core["⚙️ ais-core<br/>Zod schemas · parser · validation gateway"]
    Emit["🖨️ ais-emit<br/>llms.txt · agents.json · JSON-LD"]
    MCP["🔌 ais-mcp<br/>stdio context server"]
    Skills["🧠 ais-skills<br/>workstation-wide meta skills"]

    Profile --> Core
    Core --> Emit
    Core --> MCP
    Core --> Skills
    Emit -->|discovery surface| Bots["🤖 LLM crawlers · search · sitemaps"]
    MCP -->|routing rules + safety policy| Terminal["💻 Claude Code · Cursor · Codex sessions"]

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📦 Monorepo packages

Four decoupled, compile-safe packages under one pnpm workspace:

1. ⚙️ @frankx-ai/ais-core

• Purpose: The parser and validation gateway.
• Stack: Zod schemas, TypeScript.
• Responsibility: Parses the unified ais-profile.yaml, ensuring agent specs, skill parameters, repository boundaries, and hardware capacity constraints comply with types.

2. 🖨️ @frankx-ai/ais-emit

• Purpose: Build-time SEO & discovery generators.
• Responsibility: Compiles structural documentation:
  • llms.txt — discovery format for LLM search bots.
  • agents.json — machine-readable workspace capabilities inventory.
  • JSON-LD — Schema.org structured metadata for website sitemaps.

3. 🔌 @frankx-ai/ais-mcp

• Purpose: Live context exchange server.
• Stack: Model Context Protocol (MCP) Node.js SDK.
• Responsibility: Starts an MCP server on stdio to feed agent routing rules, workstation capacity constraints, and repository safety policies directly into developer terminal sessions.

4. 🧠 @frankx-ai/ais-skills

• Purpose: Workstation-wide meta agent skills.
• Responsibility: Houses global workspace skills (e.g. agent-manager-skill, model-routing) and distributes them dynamically to local directories (~/.agents/skills/ and ~/.claude/skills/).

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⚡ The active workstation fleet & routing protocol

AIS establishes a first-principles task-mapping system based on requirement complexity:

flowchart LR
    T["Trivial (1-3)<br/>OpenCode / Codex<br/><i>speed & minimal cost</i>"]
    M["Medium (4-6)<br/>Cursor / Cline<br/><i>interactive refinement</i>"]
    H["High (7-8)<br/>Claude Code / Antigravity<br/><i>autonomous TDD loops</i>"]
    S["Substrate (9-10)<br/>DeepAgent / SIS Swarm<br/><i>sub-agent & delegation</i>"]
    T --> M --> H --> S

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Complexity Tier	Target Agent	Primary LLM	Recommended Task Types
1-3	OpenCode / Codex	groq/llama-4-scout / gpt-4o	Single-file script edits, config modernizations, formatting, doc updates.
4-6	Cursor / Cline	Pluggable	Interactive layouts, CSS styling, component refactoring, UI adjustments.
7-8	Claude Code / Antigravity	claude-3-5-sonnet / gemini-1.5-pro	Multi-file refactors, test-driven iterations, large-context digestion.
9-10	DeepAgent / SIS Swarm	Custom / Pluggable	Long-horizon multi-step planning, remote sandbox runs, agent swarms.

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🛠️ Getting started

Prerequisites

• Node.js >= 24
• pnpm 9.x

Installation

git clone https://github.com/frankxai/agentic-intelligence-system.git
cd agentic-intelligence-system
pnpm install

Build & test

pnpm build       # build all TS packages
pnpm test        # run unit tests across packages
pnpm typecheck   # tsc --noEmit across the workspace

Run the MCP server locally

Add the server to your Claude Code / desktop config (mcp.json), pointing at your local checkout:

{
  "mcpServers": {
    "agent-intelligence-system": {
      "command": "node",
      "args": ["/abs/path/to/agentic-intelligence-system/packages/mcp/dist/index.js"],
      "env": {
        "AIS_PROFILE_PATH": "/abs/path/to/agentic-intelligence-system/ais-profile.yaml"
      }
    }
  }
}

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Built on SIP · Starlight Intelligence Protocol · MIT — see LICENSE