Readwren

WREN: AI Literary Interview Agent

**An adaptive multi-agent system that extracts your literary DNA through conversation and generates actionable reading profiles.**

WREN solves a critical problem for LLM users: you know what you like, but explaining your literary taste to an AI is hard. WREN's interview agent asks the right questions, listens deeply, and builds a structured profile that any LLM can use to generate precisely targeted content.

Built with **LangGraph**, **LangChain**, and **Kimi K2 Thinking models**.

---

Why WREN?

**The Problem**: Kimi K2 is a great writer, but users struggle to articulate their literary preferences in a way LLMs can act on. Vague prompts like "write me something good" produce generic results.

**The Solution**: WREN conducts a 12-turn adaptive interview that:

• Extracts taste anchors (what you love/hate and why)
• Maps your style signature (prose density, pacing, tone preferences)
• Identifies narrative desires (story types you wish existed)
• Captures implicit signals (vocabulary richness, engagement patterns)
• Generates a structured, machine-readable profile

**The Result**: A profile you can hand to any LLM to get content that matches your exact taste.

---

Architecture: Multi-Agent System

WREN uses a **specialized multi-agent architecture** with distinct roles:

┌────────────────────────────────────────────────────────────────────┐
│                          CLI Interface                             │
│                       (cli_interview.py)                           │
└────────────────────┬───────────────────────────────────────────────┘
                     │
       ┌─────────────┴──────────────┐
       │                            │
┌──────▼─────────────────┐   ┌──────▼──────────────────────┐
│   InterviewAgent       │   │   ProfileGeneratorAgent     │
│ (kimi-k2-thinking-     │   │   (kimi-k2-thinking)        │
│       turbo)           │   │                             │
│                        │   │ To