prompt-craft-for-comfyui-generation

id	comfyui-prompt-craft
name	Prompt craft for ComfyUI generation
summary	How to write prompts for generative models (Flux and Anima-like) in ComfyUI: two formats (Danbooru tags vs literary text), composition principles, anti-patterns and their fixes, samplers per LoRA, animation prompts. A practice-tested approach.
type	skill
author	kisa
recommended	false
added	"2026-07-04T00:00:00.000Z"
tags	["comfyui","prompting","flux","lora","generation","animation"]
source	https://mcp.deploychan.webcam/docs
description	Use when writing prompts for ComfyUI image or video models: choosing tags vs literary format, fixing composition and anatomy artifacts, picking samplers per LoRA, and writing short movement prompts for video. Neutral examples only.

Prompt craft for ComfyUI generation

A prompting approach, practice-tested on Flux and Anima-like models. The examples below are neutral; the technique applies to any content.

Two prompt formats

Format	When	Example
Danbooru tags	simple scenes, portraits, standard poses	1girl, blonde hair, sitting, park
Literary text	complex poses, unusual angles, many planes	A girl sits on the edge of a bench, adjusting her hair, seen from above

Key insight: the literary format instantly solves composition that tags can't handle — the model understands spatial relationships better in free text. Flux is especially fond of literary descriptions along the lines of "a girl stands among bushes in the middle of the street", NOT a comma-separated list of words. Caveat: some LoRA are trained only on tags — test your own stack.

Quality prefix

masterpiece, best quality, newest, highres

Avoid score_5, score_6, year 2025 — these are artifacts of other people's LoRA.

Principles (critical)

1. Composition goes in the first 3–4 tags. Angle and pose BEFORE appearance: profile, from side, sitting on chair → then hair, clothes.
2. One tag per concept. Not five synonyms for an angle — just one (from below).
3. Negatives DON'T work. The model doesn't understand no door. Describe what SHOULD be in frame, not what shouldn't.
4. Remove the conflict, don't compensate. A tag conflicts → delete it. "Fixing" tags bloat the prompt and spawn new conflicts.
5. Overloaded → rewrite from scratch. Don't patch a bloated prompt — reset to 15–20 key tags.
6. Literary drifts into photorealism → fall back to tags. If 2+ attempts produce photos or break anatomy — return to Danbooru tags (they're more reliable for simple/medium scenes).
7. Numbers in tags break the counter. double bun → hair bun, two buns. Don't mix solo and 1girl.

Anti-patterns and fixes (neutral)

Problem	Cause	Fix
Two characters instead of one	double bun (the word "double") or solo+1girl	hair bun, two buns; remove solo
Character with back to the window	front lighting + sunlight from window conflict	remove front lighting
Full body instead of close-up	sneakers, asphalt, full body pull the frame out	remove shoes/ground, keep close-up
Red instead of orange	red hair	dyed hair, orange hair
Character on the couch instead of the floor	sitting on floor, leaning against couch	sitting on armrest; remove couch
Twintails → huge bows	twintails triggers decorative ribbons	low twintails, small hair tie, elastic hair tie
Crouching instead of standing	standing without qualification	standing straight, upright
Photorealism from literary	photo terms: shot, camera, cinematic, overhead	describe the scene: seen from above, looking down at
Name collision in a batch	identical filename_prefix within a second	unique prefix per job: batch_{i}

Samplers per LoRA

Each LoRA has its own optimal sampler / scheduler / CFG — this is part of the setup, not a detail:

Sampler	Scheduler	CFG	Note
er_sde	simple	4.5	base set of style LoRA
sa_solver_pece	simple	4	Flat Color / Blending stack
euler_ancestral	beta	3.5–4	detail LoRA
euler	normal	1	Turbo-LoRA (8–12 steps)

Get exact sampler names via the API (GET /api/object_info/KSampler), don't guess: euler_a does NOT exist → the correct one is euler_ancestral; dpm++ 2M → dpmpp_2m.

Check the workflow BEFORE the prompt

Workflows get updated — the LoRA chain and node numbers change. At the start of a session:

1. Load the current API workflow (JSON).
2. Parse the LoRA chain — from the base model (UNETLoader) through all the LoraLoaders: node → file → weight → purpose.
3. Find the master-route — ImpactBoolean/ImpactSwitch, check the status (base or LoRA chain).
4. Reconcile expectations with reality — what the user thinks is active vs what's actually in the topology.
5. The SaveImage node changes ID between versions — always check before setting filename_prefix.

Animation prompts (video)

Short movement descriptions for video models:

• ULTRA-SHORT. 2–4 sentences. Only movement facts, no retelling of the scene — the video model already has the source image.
• Subject + verb. "She breathes. The hand rises. The ice rings." — bare kinetic phrases.
• Explicit causality. "The hand tucks a strand behind the ear, then lowers. The strand slips out."
• No shimmer. shimmers, flickers → a flash at frame boundaries.

Negative for video:

frame flicker, flash, brightness pulse, extra fingers, fused fingers, morphing hands, hair duplication, inconsistent lighting

Example (neutral):

She breathes slowly, swaying slightly — the ice in the glass clinks. She blinks. Her hand rises,
tucks a strand behind her ear, lowers. The strand slips out and falls onto her cheek. Her hand reaches
up to fix it again.

18+

The models and technique support 18+ content. Apply it only to consenting adults, not to real people without their consent. Comply with local laws and platform rules.