Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add MCKRUZ/ComfyUI-Expert --skill comfyui-prompt-engineergit clone --depth 1 https://github.com/MCKRUZ/ComfyUI-ExpertWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mckruz/comfyui-expert/comfyui-prompt-engineer)<a href="https://agentmods.dev/skills/mckruz/comfyui-expert/comfyui-prompt-engineer"><img src="https://agentmods.dev/badge/skills/mckruz/comfyui-expert/comfyui-prompt-engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mckruz/comfyui-expert/comfyui-prompt-engineer"><img src="https://agentmods.dev/badge/skills/mckruz/comfyui-expert/comfyui-prompt-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.01499 |
| Opus 5 | $0.00030 | $0.00749 |
| Sonnet 5 | $0.00012 | $0.00300 |
| Haiku 4.5 | $0.00006 | $0.00150 |
Grade A, and why
comfyui-prompt-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ComfyUI Prompt Engineer
Generates optimized prompts tailored to specific models and identity methods. Different models respond differently to prompts.
Model-Specific Prompt Rules
FLUX.1 (dev/schnell/Kontext)
- Style: Natural language descriptions work best
- CFG: 3.5-4 (very low)
- Quality tags: Minimal - FLUX doesn't need "masterpiece, best quality"
- Length: Medium (50-100 words)
- Structure:
{subject description}, {setting}, {lighting}, {camera/style}
Good FLUX prompt:
photorealistic portrait of a woman with auburn hair and green eyes, freckles across
her nose and cheeks, wearing a cream knit sweater, sitting in a cafe with warm ambient
lighting, shallow depth of field, shot on Sony A7IV, 85mm lens
Bad FLUX prompt (too many quality tags):
masterpiece, best quality, 8k uhd, highly detailed, photorealistic portrait...
SDXL (RealVisXL, Juggernaut, etc.)
- Style: Quality tags at front help significantly
- CFG: 7-9
- Quality tags: Include
masterpiece, best quality, photorealistic - Length: Medium-long (50-150 words)
- Structure:
{quality tags}, {trigger word}, {subject}, {details}, {setting}, {style} - Weighted syntax: Supported
(important:1.3)or((very important))
Good SDXL prompt:
masterpiece, best quality, sage_character, photorealistic portrait of a woman,
detailed skin texture with freckles, emerald green eyes, auburn copper hair,
natural lighting from window, indoor setting, shallow depth of field,
RAW photo quality, 8k uhd, film grain
SD 1.5
- Style: Tag-based works best
- CFG: 7-8
- Quality tags: Essential
- Length: Shorter (30-80 words)
- Structure:
{quality}, {trigger}, {subject}, {details}, {style tags}
Wan 2.1/2.2 (Video)
- Style: Concise motion descriptions
- CFG: 5-7
- Quality tags: Minimal
- Length: Short (20-50 words)
- Focus: Describe the motion, not just the appearance
- Structure:
{subject}, {action/motion}, {setting}, {quality}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 186 lines · 60 tokens per session scan A 821deca7374f
comfyui-prompt-engineer is a skill published in the GitHub repository MCKRUZ/ComfyUI-Expert (91 stars, last pushed 5mo ago), licensed MIT. It adds 60 tokens to every session and 1,499 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
Prompt craft for ComfyUI generation
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.
emotion-to-camera-language
A guide for turning vague visual feelings—such as cinematic, atmospheric, elegant, or healing—into concrete image or video prompt details. It uses lighting direction, depth of field, camera position, and the subject’s state.
flux-txt2img
Build Flux txt2img workflows with Flux.1 Dev (SRPO), Flux 2 Klein 9B, Turbo LoRAs, FluxGuidance, and DualCLIPLoader patterns.
prompt-engineering
ComfyUI prompt engineering knowledge covering CLIP text encoding syntax, weight modifiers, model-specific prompting strategies, and best practices.
higgsfield-seedance
Rewrites scene descriptions using professional cinematography language, structures prompts with a six-slot formula (camera + subject + action + setting + style + lighting), and diagnoses content filter rejections via a preflight linter. Use whenever the user asks for a Seedance 2.0 / Seedance Pro prompt, describes a…
higgsfield-acting
Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a…