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/krea2-txt2img

Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting

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comfyui-mcp
74242 skills4 agents11 commands1 MCP
Install
$ npx -y skills add artokun/comfyui-mcp --skill krea2-txt2img --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/krea2-txt2img

Context preview

The summary Claude sees to decide when to auto-load this skill.

Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting

SKILL.md

krea2-txt2img.SKILL.md
name: krea2-txt2img
description: Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting
globs:
  - "**/*.json"

Krea 2 Text-to-Image Workflows

Overview

Krea 2 is a **12B-parameter Diffusion Transformer** from Krea.ai (released June 2026, weights open-sourced under the Krea 2 Community License, free commercial use up to 50 seats). Two variants:

1. **Krea 2 Raw** is the base checkpoint before extra post-training. For fine-tuning / maximum fidelity, more steps. 2. **Krea 2 Turbo** is post-trained and **distilled**; it generates in **~8 steps at cfg 1**. This is what the krea2 txt2img packs ship.

Three packs (V2 — no group toggles)

Sliced from the **KREA2 ULTRA V2** monolith into standalone single-pipeline packs. Pick by how you prompt and what you want:

  • **`krea2-txt2img-manual`**: plain prose prompt (the `MANUAL PROMPT` node).
  • **`krea2-txt2img-json`**: Ideogram-4-style structured JSON / area prompting

(`Ideogram4PromptBuilderKJ`).

  • **`krea2-combo`**: two-pass **detail boost**, a first pass then a low-denoise

refine (denoise 0.3), with the krea2 **turbo LoRA** @0.2 on both passes plus the optional **IdeoKrea** LoRA. JSON/Ideogram-style prompting; saves both passes to compare.

Each pack's one prompt source is active (no prompt-mode bypass to flip). `ImageSharpenKJ` runs before `SaveImage`. **V2** adds the `Krea2T-Enhancer` MODEL detail-boost patch (ships **active**) and drops v1's `ConditioningKrea2Rebalance`. `RBG_Smart_Seed_Variance` ships **bypassed** (optional, see below).

Krea 2 has **native ComfyUI support** (`comfy/text_encoders/krea2.py`, ComfyUI ≥ v0.26.0). The `CLIPLoader` uses **`type=krea2`**, with a **Qwen3-VL 4B** text encoder and the **Qwen image VAE**. The Qwen3-VL encoder drives strong prompt adherence and structured-JSON prompts.

Models (all from the `Aitrepreneur/FLX` mirror; official: `krea/Krea-2-Turbo`)

| Slot | File | Notes | |---|---|---| | `diffusion_models/` | `krea2_turbo_fp8.safetensors` | 12B Turbo, fp8 — RTX 4000/3000/2000 | | `diffusion_models/` | `krea2_turbo_mxfp8.safetensors` | RTX 5000 (Blackwell) native fp8 | | `text_encoders/` | `qwen3vl_4b_fp8_scaled.safetensors` | Qwen3-VL 4B encoder | | `vae/` | `qwen_image_vae.safetensors` | Qwen image VAE | | `loras/` | `krea2_turbo_lora_rank_64_bf16.safetensors` | turbo LoRA — **combo** only, @0.2 both passes | | `loras/` | `IdeoKrea-test.safetensors` | OPTIONAL Ideogram-style LoRA (`Aitrepreneur/IdeoKrea`) — combo add-in |

Node stack

  • **core**: `UNETLoader` (krea2_turbo) → `CLIPLoader` (type=krea2) → `VAELoader`

(qwen_image_vae), wired via KJNodes `SetNode`/`GetNode` buses into a subgraph (`CLIPTextEncode` → `KSampler` → `VAEDecode`). An rgthree `Any Switch` sits in front of the encoder; in each pack only that pack's prompt source is wired to it (manual node in `-manual`, JSON builder in `-json`).

  • **rgthree-comfy**: Power Lora Loader, Any Switch, Label, Fast Groups.
  • **ComfyUI-KJNodes**: Set/Get, `Ideogram4PromptBuilderKJ`, `ImageSharpenKJ`, `INTConstant`.
  • **ComfyUI-Krea2T-Enhancer** (`capitan01R`): `Krea2T-Enhancer`, the **V2** MODEL→MODEL

detail-boost patch, wired in the model path (PowerLora → Krea2T-Enhancer → sampler). Ships **active**; bypass to compare against the un-boosted result.

  • **ComfyUI-RBG-SmartSeedVariance**: `RBG_Smart_Seed_Variance`, **optional**, ships

**bypassed** in the positive-conditioning loop.

  • **ComfyUI_essentials** (`cubiq`): `ImageResize+`, **combo** only (the two-pass

VAE-roundtrip resize).

Settings that matter

  • **steps 8, cfg 1.** Turbo is distilled; more steps or higher cfg over-cooks it.
  • **sampler `er_sde`, scheduler `simple`** are the verified defaults.
  • **1920×1080** default; Krea 2 handles a wide aspect range.
  • The prompt source is fixed per pack (manual node vs JSON builder). There is no

prompt-mode bypass to flip.

V2 detail boost (`Krea2T-Enhancer`) + combo

  • **`Krea2T-Enhancer`** is a MODEL→MODEL patch (the V2 "massive detail boost"). It

sits inline in the model path and ships **active** in all three packs. Widgets are `[on, strength, …]`; bypass it (or toggle `on`) to A/B the boost.

  • **`krea2-combo`** is the full demonstration of the boost, a two-pass refine:

FIRST PASS (8 steps, `er_sde`, denoise 1) → VAE roundtrip → SECOND PASS (4 steps, `euler`, denoise **0.3**), with the **turbo LoRA** @0.2 on both passes. It SAVES BOTH passes so you can see the boost. The **IdeoKrea** LoRA is downloaded but NOT wired by default. Drop it into the Power Lora Loader's empty slot (start ~0.5 to 1.0; it's a test LoRA) for the turbo + IdeoKrea Ideogram-style combo.

Optional post-proc (ships bypassed — un-bypass to use)

All packs leave `RBG_Smart_Seed_Variance` in the positive-conditioning loop **bypassed** (passthrough). Un-bypass on the live canvas with `panel_set_node_mode` (or in the UI) for controlled variations of the same prompt without changing the composition. Set its seed mode to `randomize` and tune the variance mode (e.g. `🌿 Balanced`) / strength widgets. Leave bypassed for a deterministic result.

JSON / area prompting

Like Ideogram 4, Krea 2's Qwen3-VL encoder reads structured prompts (per-region desc + bounding boxes + palettes). For structured prompting use the **`krea2-txt2img-json`** pack; its `Ideogram4PromptBuilderKJ` drives the encoder directly (no bypass to flip). After the render, VERIFY the image matches the JSON you set (view it) BEFORE continuing; if it doesn't, a field is probably stale. Fix and rerun. Gotchas learned the hard way:

  • **Set ALL the builder fields**, not only the prompt/boxes: `background`,

`technical`, `style`, `lighting` (widgets 3/5/6/7). Leaving stale values leaks content (a leftover celebrity portrait bled into a tea still-life).

  • **Keep palettes minimal or empty.** A top-level palette with many colors can render as a

li

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