comfyui

comfyui is a skill for Claude Code, Codex from metaspartan/cybara. It costs 48 tokens per session (738 once invoked), scanned A, original, MIT.

A controller for ComfyUI, a node-based local system for generating and editing images with Stable Diffusion models.

In plain words
What is it for?
Use it for text-to-image generation, image-to-image edits, inpainting, upscaling, and custom image workflows.
Why use it?
It lets an agent submit image-generation workflows and retrieve their results through ComfyUI's HTTP interface.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

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.

agentmods
npx agentmods add skills/metaspartan/cybara/comfyui
Any agent
npx skills add metaspartan/cybara --skill comfyui
Clone the repo
git clone --depth 1 https://github.com/metaspartan/cybara

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for comfyui

README.md
[![agentmods](https://agentmods.dev/badge/skills/metaspartan/cybara/comfyui.svg)](https://agentmods.dev/skills/metaspartan/cybara/comfyui)
Your own site
<a href="https://agentmods.dev/skills/metaspartan/cybara/comfyui"><img src="https://agentmods.dev/badge/skills/metaspartan/cybara/comfyui.svg" alt="Measured on agentmods" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 738 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.00738
Opus 5 $0.00024 $0.00369
Sonnet 5 $0.00010 $0.00148
Haiku 4.5 $0.00005 $0.00074

Measured 6d ago against content hash 91270bba330c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

comfyui 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 6d 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.

skills/comfyui/SKILL.md · 47 lines

How it starts

The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ComfyUI

ComfyUI is a node-based Stable Diffusion pipeline with an HTTP API. Generate images by posting a workflow (prompt graph) and polling for results.

When to use

  • "generate an image of … (via ComfyUI)"
  • img2img, inpainting, upscaling, or custom SDXL/Flux workflows.
  • The user references ComfyUI explicitly or has it installed.

How it works

  1. Build a workflow graph as JSON (prompt API). Each node has a class_type and inputs. A minimal txt2img graph: CheckpointLoader → CLIPTextEncode (pos/neg) → EmptyLatentImage → KSampler → VAEDecode → SaveImage.
  2. Submit: POST /prompt with {"prompt": <graph>, "client_id": <id>}. Returns a prompt_id.
  3. Poll history: GET /history/<prompt_id> until the output image(s) appear, then fetch from /view?filename=….
  4. Save outputs to the workspace and state their paths.

Minimal node template (txt2img)

{
  "3": { "class_type": "KSampler", "inputs": {
      "seed": 42, "steps": 25, "cfg": 7, "sampler_name": "euler", "scheduler": "normal",
      "denoise": 1, "model": ["4",0], "positive": ["6",0], "negative": ["7",0],
      "latent_image": ["5",0] } },
  "4": { "class_type": "CheckpointLoaderSimple", "inputs": { "ckpt_name": "sdxl_base.safetensors" } },
  "5": { "class_type": "EmptyLatentImage", "inputs": { "width": 1024, "height": 1024, "batch_size": 1 } },
  "6": { "class_type": "CLIPTextEncode", "inputs": { "text": "<prompt>", "clip": ["4",1] } },
  "7": { "class_type": "CLIPTextEncode", "inputs": { "text": "<negative>", "clip": ["4",1] } },
  "8": { "class_type": "VAEDecode", "inputs": { "samples": ["3",0], "vae": ["4",2] } },
  "9": { "class_type": "SaveImage", "inputs": { "filename_prefix": "cybara", "images": ["8",0] } }
}

Notes

  • Default server: http://127.0.0.1:8188 (override via the request URL).
  • Use the http tool to submit/poll; you don't need raw fetch.
  • For img2img/inpaint, add LoadImage + replace EmptyLatentImage; lower denoise (~0.5–0.75) to keep structure.
  • Always state the server URL and output path in your response.

Read the full file on GitHub · 47 lines

Changes

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.

  1. 6d ago First seen · 47 lines · 48 tokens per session scan A 91270bba330c

Subscribe to this mod's changes

comfyui is a skill published in the GitHub repository metaspartan/cybara (26 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 738 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright…

google/adk-js · 62 tokens

kodama-verification

Define measurable success criteria and collect targeted test, build, lint, type-check, or smoke-test evidence before claiming work is complete.

amergrgic/kodama · 31 tokens

gh-issues

Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5]…

google/adk-js · 116 tokens

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project…

google/adk-js · 67 tokens

kodama-behavior

Classify requests, assess unfamiliar codebases, delegate work safely, and recover from failed attempts. Use for multi-step, ambiguous, or parallelizable work.

amergrgic/kodama · 37 tokens

kodama-constraints

Enforce non-negotiable safety, scope, security, and quality constraints for implementation and review work.

amergrgic/kodama · 26 tokens