# Idea 001: Visual Narrative Agent

**Date:** 2026-04-19  
**Status:** Idea  
**Tags:** hermes-agent, kimi-vision, storytelling, image-generation

## Concept

An agentic storytelling system where Hermes orchestrates a narrative loop with Kimi's visual analysis and built-in image generation skills to produce coherent visual stories.

## User Flow

1. User provides text prompt (e.g., "A lone astronaut discovers an ancient alien garden on Mars")
2. Hermes plans story structure (scenes, pacing, visual style)
3. For each scene:
   - Hermes generates image prompt
   - Generate image (Hermes built-in skill: manim / ascii)
   - Kimi analyzes generated image
   - Kimi's feedback refines next scene's prompt
4. Return compiled visual story to user

## Key Differentiator

Most story-to-image tools: **Generate → Done**

This concept: **Generate → Analyze → Refine → Loop**

Kimi serves as the **visual reasoning engine** — tells Hermes if the generated image matches the intended scene, catches inconsistencies, and informs prompt refinement for the next scene.

## Tech Stack

| Component | Source | Role |
|-----------|--------|------|
| Hermes Agent | Nous Research | Orchestration, planning, decision loop |
| Kimi Vision | Moonshot AI (via gateway) | Image analysis, visual feedback |
| Image Generation | Pollinations AI | Free tier, multiple models (Flux, etc.) |

### Image Generation Options

| Provider | Free Tier | Quality | Use Case |
|---------|-----------|---------|----------|
| **Pollinations** ✅ | ✅ Yes | Good | Primary (simple, free) |
| **Flux (local)** | ✅ Free | High | If GPU available |
| **Hermes skills** | ✅ Free | Niche | Fallback/ASCII aesthetic |

### Pollinations API (Primary)
- **Endpoint:** `https://gen.pollinations.ai/image/{prompt}`
- **Models:** flux, zimage, wan-image, qwen-image, etc.
- **Cost:** Free tier (pollen credits), ~$1/1 Pollen paid
- **Auth:** Optional for free tier

## Strengths

- ✅ Combines Hermes + Kimi + Pollinations natively
- ✅ Agentic visual feedback loop is unique
- ✅ Visual coherence check via Kimi ensures quality
- ✅ Free tier = low barrier to test
- ✅ User controls output format (default: image)

## Weaknesses

- ⚠️ Pollinations quality vs DALL-E/Midjourney (may need to test)
- ⚠️ Kimi requires gateway access (no direct API key)
- ⚠️ Loop adds latency (generate → analyze → refine)
- ⚠️ Need to verify Pollinations reliability

## Uniqueness Score

**7/10** — Agentic visual feedback loop is novel, but need to verify if built-in image generation is compelling enough

## Next Steps

- [ ] Explore Hermes built-in image skills (manim, ascii)
- [ ] Define output format options
- [ ] Sketch technical architecture

## Related Ideas

- See: `002-xxx.md`, `003-xxx.md` for alternatives