Lay out and organize a ComfyUI workflow cleanly on the live panel canvas — dependency-layered node placement with no overlaps, subgraphs, colored group boxes, and subgraph rail alignment. Use when asked to tidy / clean up / organize / arrange a workflow, add groups or subgraphs, fix overlapping nodes, or build a workflow that should look good from the start.
npx skills add https://github.com/artokun/comfyui-mcp --skill workflow-layout
Turn a tangled graph into a clean left-to-right dataflow a human reads at a glance,
using the panel_* canvas tools. The golden rule: never lay out blind — read the
real node sizes and rail positions first, then compute positions from them.
panel_query_graph {fields:'detail', limit:200, max_chars:60000} — READ FIRST, every time. Returns, for the graph you're viewing:pos [x,y], size [w,h] (body only), and full_height (theTRUE rendered footprint = title bar + body; use this for vertical stacking),
groups (id, title, color, bounding [x,y,w,h]),rails: the input / output boundarynode positions. Everything below is computed from these numbers.
panel_edit_node({node_id, pos?, size?, title?, collapsed?, preset?|color?|bgcolor?})atomically moves, resizes, retitles, collapses, or color-codes a node. Widget
values remain on their dedicated tool; execution mode is available as mode when needed.
panel_create_group (pass node_ids toauto-wrap, or bounds [x,y,w,h]; color hex), panel_move_group, panel_edit_group,
panel_remove_group.
panel_create_subgraph(node_ids),panel_enter_subgraph / panel_exit_subgraph, panel_get_subgraph,
panel_promote_widget, panel_move_rail(rail, [x,y]) (rail = "input"|"output",
must be inside the subgraph), panel_expose_subgraph_output(from_node_id, from_output) /
panel_expose_subgraph_input(to_node_id, to_input) (expose an interior slot on the
boundary rail — must be inside the subgraph), and panel_unpack_subgraph(node_id)
(expand/dissolve a subgraph back into the parent — the inverse of panel_create_subgraph).
panel_canvas({action:"fit"}) to frame the result; panel_save_workflow to persist.connected_from (ignore unconnectedwidget inputs — only node→node edges matter).
layer(n) = 0 if it has no incoming node edges, else 1 + max(layer(of its sources)).
Layers become columns, left → right.
x = X0 + layer * COL_PITCH, where `COL_PITCH ≈ widest node.size[0] inthat column + ~80`.
y[i+1] = y[i] + node[i].full_height + ROW_GAP. Use full_height (from
panel_query_graph detail rows), NOT size[1]. size[1] is the BODY only (slots + widgets); the
title bar renders ~30px ABOVE pos and is NOT in size[1], so stacking by size[1]
overlaps every node by a header (the classic "headers eating the node above" bug).
full_height already includes that header (and is just the title height for a collapsed
node), so y += full_height + ROW_GAP lands an exact ROW_GAP gap between the previous
node's bottom and the next node's title. Never use a fixed row pitch — tall nodes
(KSampler, WanVideo Sampler, LoRA-select) are 480–600px and *will* overlap a 320 pitch.
(If full_height is ever absent, fall back to size[1] + ~30 for the header.)
connected nodes (a median/barycenter pass is plenty).
Reads-well constants: COL_PITCH 360–480, ROW_GAP 40. Because full_height already
accounts for the title bar, you don't add extra top headroom per node — ROW_GAP is the
clean gap you'll actually see.
A subgraph has two boundary rails (input left, output right). They do not follow the
inner nodes — move the nodes without moving the rails and you get a huge gap (a very common
mistake). For each subgraph: panel_enter_subgraph → lay out the inner nodes (algorithm
above) → then pin the rails to the node band:
panel_move_rail("input", [minNodeX - 180, bandTopY])panel_move_rail("output", [maxNodeX + 60, bandTopY])Keep rails at the same Y as the first row. Read current rail positions from
panel_query_graph (rails) before deciding. panel_exit_subgraph when done.
Wiring interior nodes to the boundary (don't connect to a guessed rail id). To expose
an interior node's output/input on the boundary so the PARENT graph can wire it, do NOT
panel_connect to a rail node id you guessed — use `panel_expose_subgraph_output(from_node_id,
from_output) (interior output → output rail) and panel_expose_subgraph_input(to_node_id,
to_input) (interior input → input rail), both while inside the subgraph. panel_query_graph`'s
rails shows which boundary slots already exist and which still need exposing. To expand/
dissolve a subgraph back into the parent (inline its inner nodes + rewire external links,
removing the wrapper — the inverse of panel_create_subgraph), use
panel_unpack_subgraph(node_id). All undoable with Ctrl+Z.
for this first — to label regions of a flat graph or band stage-columns at the root.
nodes and adds boundary ports. Don't subgraph everything — a 2–3 node stage rarely earns
it, and over-subgraphing hurts readability and complicates packaging/handoff.
subgraphs → drop colored group bands around the columns at the root.
`Loaders → Inputs → Preprocess (pose/controlnet/conditioning) → Embeds → Sample →
Decode/Output` — one concern per column/stage, strictly left-to-right.
The nodes a user touches first — the input (Load Image / Load Video) and the
output (save / video-combine / preview) — must stay expanded and visible so they
can jump straight in: drop in their media, hit run, watch the result. Collapse the
internal machinery (loaders, encoders, samplers) into chips to cut noise, but never
collapse the inputs or outputs. When they live inside subgraphs, keep those subgraph
nodes expanded — and consider panel_promote_widget to surface the one key widget
(prompt, seed) onto the subgraph node so it's editable without drilling in.
> Heads-up: input/output preview nodes (LoadImage, VHS_LoadVideo, video-combine)
> report their full size[1] but render short until media loads — size their group band
> to the .size (so it fits once filled), not to the empty-preview render.
panel_query_graph {fields:'detail', limit:200, max_chars:60000} — capture pos/size/groups (and rails inside each subgraph).panel_edit_node for each node (or bulk only when the same presentation change is intended).panel_move_rail both rails → exit.panel_create_group bands around the root columns (and panel_remove_groupany stranded empty groups left behind by earlier edits).
panel_save_workflow, then panel_canvas({action:"fit"}).browser refresh reloads from the saved workflow (and re-binds nodes after installing packs).
LoadImage, VHS_LoadVideo, preview nodesreturn a tiny size[1] because the image/video preview height isn't in .size. Leave
extra vertical room (≈250–300px) below them so the preview doesn't overlap the next node.
blue, sampler green) and collapsed rarely-touchedloaders to cut visual noise — cheap wins once the positions are right.
Generate breadboard circuit mockups and visual diagrams using HTML5 Canvas drawing techniques. Use when asked to create circuit layouts, visualize electronic component placements, draw breadboard diagrams, mockup 6502 builds, generate retro computer schematics, or design vintage electronics projects. Supports 555 timers, W65C02S microprocessors, 28C256 EEPROMs, W65C22 VIA chips, 7400-series logic gates, LEDs, resistors, capacitors, switches, buttons, crystals, and wires.
> Use when a HyperFrames composition needs seek-safe 2D/3D keyframes, GSAP timelines, CSS keyframes, Anime.js, WAAPI, FLIP, paths, masks, SVG morph/draw, text trails, 3D depth, or `hyperframes keyframes` diagnostics. Don't use for broad scene strategy, brand design, media sourcing, captions, or general video planning.
Analyze images, websites, and Figma files to extract their design and generate a `design.md` with token system, component inventory, and reconstruction notes. Use this skill whenever the user wants to understand, document, replicate, or audit the design of something visual: a screenshot, a URL, a Figma link, a Pinterest reference, a mockup, a competitor's site, a component, a dashboard, a landing page. Also when they ask 'extract the design system from X', 'document the style of Y', 'analyze this visually', 'convert this image into tokens', 'help me replicate this design', 'what palette does this site use', 'how is this built'. Also for single elements: 'copy this navbar', 'recreate this illustration', 'give me a prompt to regenerate this graphic' — element mode outputs a focused element.md, with token-grounded image-model prompts when the element is visual art. If the user brings any visual source and wants to understand it at a design level — this skill should activate.
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write code.
Optimize web performance: bundle size, images, caching, lazy loading, and overall page speed. Use when site is slow, reducing bundle size, fixing layout shifts, improving Time to Interactive, or optimizing for Lighthouse scores. Triggers on: web performance, bundle size, page speed, slow site, lazy loading. Do NOT use for Core Web Vitals-specific fixes (use core-web-vitals), running Lighthouse audits (use perf-lighthouse), or Astro-specific optimization (use perf-astro).
| Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
| Official GSAP skill for performance — prefer transforms, avoid layout thrashing, will-change, batching. Use when optimizing GSAP animations, reducing jank, or when the user asks about animation performance, FPS, or smooth 60fps.
Take artokun/workflow-layout from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.