Ecosystem

How It All Connects

The Arkos ecosystem follows a skill-per-problem architecture: each tool is focused on one domain, and they compose through Conductor rather than being bundled into a monolithic platform.

The Flow

Developer → AI Coding Agent (Claude Code / Cursor / Codex)
    ↓
Apollo (enforces project conventions)
    ↓
Conductor (classifies task → selects pipeline → sequences skills)
    ↓
[Build Phase] → Code written by AI agent
    ↓
Carto (indexes codebase → 7-layer knowledge graph)
    ↓
Memories (stores index, learnings, context across sessions)
    ↓
Delphi (generates test scenarios from built software)
    ↓
Hermes (generates docs for internal, external, marketing audiences)
    ↓
Learning-Skill (captures failures and fixes for future sessions)

Layer Architecture

Infrastructure Layer

Memories stores everything. Every other tool reads from or writes to Memories — codebase indexes (Carto), test results (Delphi), learnings (Learning-Skill), project conventions (Apollo).

Carto builds a 7-layer semantic map of your codebase and stores it in Memories. Other tools query this map to understand code structure without re-reading files.

SwarmEngine orchestrates multiple AI agents in parallel or sequential DAGs. Uses PersonaSmith personas to give agents specialized roles.

Workflow Layer

Conductor is the entry point. It reads your task, classifies it (quick fix, feature, complex/0-to-1), and routes it through the right pipeline of skills.

Apollo enforces project conventions by injecting them into every agent’s instruction file. It works across Claude Code, Cursor, Codex, and other AI tools.

Quality Layer

Delphi generates guided test scenarios (positive, negative, edge, accessibility, security) and can execute them via browser automation.

Hermes generates documentation for three audiences from a single codebase: internal (CS/Support), external (users/devs), and marketing.

Learning-Skill auto-captures failures and their fixes, storing them in Memories so you never repeat the same mistake across sessions.

Agent Layer

PersonaSmith provides 75 research-backed AI agent personas across 15 enterprise departments, ready for use with SwarmEngine.

Design Principles

1. Specialized tools over monolithic platforms — each tool does one thing well
2. Compose through orchestration — Conductor wires tools into pipelines
3. Memory as the backbone — Memories is the shared state layer
4. Agent-agnostic — works with Claude Code, Cursor, Codex, and others