Comfyui Skill Openclaw
HuangYuChuh/ComfyUI_Skills_OpenClaw
Run registered ComfyUI workflows through the fast comfyui-skill CLI, and use the official local Comfy MCP for live template, node, model, validation, and orchestration capabilities.
Turn a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI instance — reuses the same topology model as threejs-network-viz (any of 8 topology-source integrations…
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install automateyournetwork/netclaw comfyui-topology-viz --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .claude/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .claude/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-vizType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install automateyournetwork/netclaw comfyui-topology-viz --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .agents/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .agents/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install automateyournetwork/netclaw comfyui-topology-viz --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .cursor/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .cursor/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/automateyournetwork/netclaw.git --path workspace/skills/comfyui-topology-viz--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install automateyournetwork/netclaw comfyui-topology-viz --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .gemini/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .gemini/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install automateyournetwork/netclaw comfyui-topology-vizInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .github/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .github/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install automateyournetwork/netclaw comfyui-topology-viz --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/workspace/skills/comfyui-topology-viz .opencode/skills/comfyui-topology-viz && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "comfyui-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/comfyui-topology-viz into .opencode/skills/comfyui-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comfyui-topology-viz", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
comfyui-topology-vizTurn a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI instance — reuses the same topology model as threejs-network-viz (any of 8 topology-source integrations…
Comfyui Topology Viz is an agent skill from automateyournetwork/netclaw. Turn a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI instance — reuses the same topology model as threejs-network-viz (any of 8 topology-source integrations, or a freeform description). Use when the operator asks for a stylized, flashy, or AI-generated image/picture/illustration of a network topology. Stills only — no video/animation.
Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files (for example `__init__.py`, `comfyui_client.py` and `federated_generation.py`).
It sits in AI & LLM Engineering, covering Diffusion and image models and 3D graphics and WebGL. It works with ComfyUI, Three.js and Model Context Protocol. The repository describes itself as: An AI agent that claws through your network. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit aa90e7d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships script files (Python), which the agent can run.
Shell commands in SKILL.md call:
npmFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Comfyui Topology Viz loads about 3.9k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 1,872 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- **`COMFYUI_URL`** in `.env` (see `.env.example`) — your ComfyUI instance's endpoint, e.g.Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from automateyournetwork/netclaw at commit aa90e7d, republished under its Apache-2.0 licence (© automateyournetwork). 1,872 words, ~3,903 tokens.
.claude/skills/comfyui-topology-viz/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.Version: 1.0.0 Feature: 120-comfyui-topology-viz Status: Active
Turns a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI
instance — a different rendering path from NetClaw's existing three.js (threejs-network-viz),
Blender (blender-3d-viz), and UE5 (ue5-network-viz) skills, which all produce navigable 3D
scenes. This skill produces one flat, "flashy" illustration per request instead, reusing the same
canonical topology model spec 046's three.js skill already assembles from any of NetClaw's
existing topology-source integrations, or a freeform description.
v1 scope is stills only. Video (traffic flybys, packet-tracing animations) and stylized test-result cards are explicitly out of scope for this version — likely follow-on specs, not built here (spec.md FR-016).
COMFYUI_URL in .env (see .env.example) — your ComfyUI instance's endpoint, e.g.
http://127.0.0.1:8000. Required; there is no assumed default (FR-005), because
comfyui-mcp's own built-in defaults (8000 for ComfyUI Desktop, 8188 for a manual install)
are easy to mix up with your actual instance's port.comfyui-mcp server (mcp-servers/comfyui-mcp/), cloned and built via
npm install && npm run build, registered as comfyui-mcp in config/openclaw.json.Any of NetClaw's existing topology-of-record or lab-emulation integrations — Cisco Modeling Labs, GNS3, containerlab, EVE-NG, Nautobot, NetBox/Infrahub, IP Fabric, or Forward Networks — or a freeform plain-language description requiring no live source at all.
"Give me a stylized AI image of the CML lab topology"
"Render my GNS3 project as a ComfyUI image"
"Make a flashy image of this network"NetClaw retrieves the topology from the named (or clarified) source, checks what image-generation
checkpoints ComfyUI has installed, generates one image, and tells you where it was saved:
workspace/output/comfyui-topology-viz/comfyui-<timestamp>-<request-id>.png (plus a sidecar
.json recording the prompt and checkpoint used) — and which checkpoint was used (FR-006a).
"Make a flashy image of this topology: a router r1 connected to a switch sw1"Same generation pipeline as a live-sourced request, just parsed from your plain-language description instead.
Every failure NetClaw can detect gets a specific, distinct message — never a hang or a generic error:
| Condition | What NetClaw tells you |
|---|---|
ComfyUI unreachable at the configured COMFYUI_URL (or comfyui-mcp silently connected to a different instance instead — see Known Limitations) | The configured endpoint could not be reached |
| ComfyUI reachable, but no installed checkpoint is suitable for image generation | What kind of model to install (SD1.5/SDXL/Flux) and where |
| ComfyUI itself reports the generation job failed | The generation failed — as distinct from a reachability or missing-model problem |
| A generation is already running | Wait for it to finish (or fail) and ask again — this skill runs one job at a time, never two concurrently |
| A named topology source is unreachable | The sourcing failure, distinct from anything ComfyUI-side |
| The topology has zero devices | Nothing to visualize — no generation is attempted |
There is no NetClaw-imposed timeout on generation itself — real GPU image-generation time varies with model, workflow, and hardware, so a submitted job is tracked to ComfyUI's own completed/failed status rather than being given up on early.
Expected on a fresh ComfyUI install with no checkpoints downloaded yet — not a NetClaw bug. Install
at least one Stable Diffusion 1.5, SDXL, or Flux checkpoint into ComfyUI's models/checkpoints
directory (ComfyUI Manager, or a manual download into that folder), then ask again.
| Module | Responsibility |
|---|---|
topology_model.py | Canonical Device/Interface/Link/TopologySnapshot types (ported from threejs-network-viz, trimmed of 3D-only concepts) |
materials.py | Hostname-based device-role inference (ported, trimmed of color tables) |
sources.py | One adapter per topology source (8 live integrations + freeform), plus source-selection disambiguation (ported) |
generation_model.py | NEW entities: GenerationRequest, ModelAvailabilityCheck, GeneratedImage, the six-kind GenerationFailure taxonomy |
comfyui_client.py | MCP stdio client wrapper around the vendored comfyui-mcp server — discovery, template selection, async submission, no-timeout polling, plus the ControlNet workflow builder and image upload |
prompt_builder.py | TopologySnapshot → a bounded-length, role/count-summarized generation prompt |
topology_renderer.py | Deterministic (NOT AI) box/line structure diagram, fed to ComfyUI's Canny node as ControlNet conditioning — the structural-accuracy pipeline (research.md §10) |
label_overlay.py | Burns real, correct hostname labels onto the completed generation deterministically — Canny-conditioned text is too lossy for Flux to reproduce reliably (research.md §10) |
generation.py | Orchestrates the full call sequence and every failure classification; picks the structural ControlNet path when available, falls back to plain txt2img otherwise; enforces the single-in-flight-job guard — unmodified since spec 120 (spec 121 FR-012) |
output.py | Overlays labels (if structural path used) and copies the completed image into workspace/output/comfyui-topology-viz/ with a timestamped name + sidecar JSON, never overwriting — unmodified since spec 120 |
federated_generation.py | NEW (spec 121) — the actual entry point __init__.py now calls. Routes each request between the federated path (below) and generation.run_generation()'s existing pipeline (called as-is, never modified) |
See contracts/comfyui-generation-contract.md for spec 120's exact fallback call sequence, and
specs/121-federated-topology-viz/contracts/ for the two new federated-stage tool contracts.
Same entry point, no new command — every "give me a stylized image" request goes through this
skill exactly as before; which path actually produced the delivered image is now visible in the
response as generation_path:
generation_path | Meaning |
|---|---|
federated | Both stages ran on an operator-configured federation member (e.g. <your-risk>/viz): a deterministic, correct-by-construction diagram (real role icons, real labels, real connections — no diffusion model involved), then a diffusion image-edit pass that restyled it without altering structure. This is the strongest correctness guarantee this skill can offer (spec 121 SC-001). |
federated_partial | The structural diagram (correct, unstyled) was produced on the configured federation member, but the styling stage failed or that half of the member was unreachable — you still get the correct diagram, not nothing, with reason telling you styling didn't complete. |
fallback | Spec 120's original Flux+ControlNet+Canny pipeline (unchanged) — used for a freeform request (no real device data for the structural stage to work from) or when the configured federation member itself is unreachable. reason says which. |
Both new stages run as separate MCP servers (mcp-servers/topology-diagram-mcp/,
mcp-servers/image-style-mcp/) invoked from Border via n2n/tools/call on the live
your configured federation member — Border never renders or diffuses anything itself for this path (FR-005).
See specs/121-federated-topology-viz/research.md for the full design, including four real gaps
found and fixed in the shared federation infrastructure itself (R10) to make this actually work —
this was the first working internal n2n/tools/call in the codebase.
If your viz federation member is down: systemctl --user start netclaw-member-<your-risk>-viz.service (service name derived from your own risk/member name, per your N2N federation setup)
(it's enabled, so a host reboot brings it back automatically).
| Variable | Required | Purpose |
|---|---|---|
COMFYUI_URL | Yes | Endpoint of your own already-running ComfyUI instance |
comfyui-mcp can silently substitute a different ComfyUI instance than the one configured.
Found live during implementation: if the configured COMFYUI_URL is unreachable, comfyui-mcp
falls back to port-scanning common local ports and connects to whatever ComfyUI it finds there
instead of failing — even for a completely non-routable configured host. comfyui_client.py
guards against this by verifying the response's comfyuiUrl/discoverySource actually match
what was configured, treating a mismatch as backend_unreachable rather than silently
generating against the wrong instance. See research.md §8. If you run more than one ComfyUI
instance on the same network, double-check COMFYUI_URL is exactly right.comfyui-mcp's own npm audit reports 10 vulnerabilities (1 low, 2 moderate, 7 high) in
transitive dependencies it bundles for its own internal HTTP/WebSocket handling (hono,
path-to-regexp, qs, sharp, ws) — all in libraries used for comfyui-mcp's own internal
serving/media-processing, not exposed to this skill's stdio-only, sandboxed usage. Tracked as a
non-blocking follow-up, matching the same treatment sketchfab-mcp-server's own audit findings
received in spec 046 — do not run npm audit fix --force (it force-upgrades sharp with a
breaking change) without testing the server still builds and runs afterward.comfyui-mcp's own task tracker (get_task_result/get_task/list_tasks) is unreliable —
do not poll it. Live-verified: it got permanently stuck reporting {"status": "working"} for
a job ComfyUI itself had already completed successfully ~19 seconds earlier; its WebSocket
completion listener silently failed to update. Completion is instead tracked by polling
ComfyUI's own /history/{promptId} endpoint directly (comfyui_client.get_prompt_history()),
and the finished image is downloaded straight from ComfyUI's own /view endpoint — neither
depends on anything comfyui-mcp reports about task status or file location. See research.md
§9. get_task_result is kept in comfyui_client.py for diagnostics only.run_workflow intermittently raised anyio.BrokenResourceError even though the job had
actually submitted and completed successfully every time (confirmed against ComfyUI's own
history) — a race between trailing stdio traffic and our client's async with teardown. Fixed
by capturing the result before the context managers close (research.md §9).sd_xl_base_1.0.safetensors, correctly attributed in both
the returned path and the sidecar JSON — but visually confirmed not to resemble the actual
topology (abstract line-art, no real structure).sources.from_freeform() mis-parsed connector clauses with inline role declarations.
"core1 connects to a switch called sw1" took the article "a" as the device name instead of
"sw1" — creating a phantom device and leaving the real one disconnected. Invisible in the plain
path (which never exposes exact link structure in its prompt) but exposed immediately once the
structural renderer made the parsed graph directly visible. Fixed in sources.py; the identical
bug still exists in threejs-network-viz/sources.py (this was ported from there) but was left
untouched per FR-014. See research.md §10.label_overlay.py. See research.md §10.core1↔sw1↔fw1 chain, correct
legible labels. Remaining imperfections are cosmetic (generic device icons rather than
role-specific ones, decorative hallucinated background clutter, thin/dashed rather than
"glowing" connection lines) — prompt-tuning opportunities, not correctness bugs.specs/120-comfyui-topology-viz/model-inventory.md for the full list and cleanup guidance if
disk space is needed back.See specs/120-comfyui-topology-viz/tasks.md for the full implementation history and
research.md for the technical decisions and live findings behind this skill's design.
© automateyournetwork, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 12 other files in workspace/skills/comfyui-topology-viz of automateyournetwork/netclaw.
Open the folder on GitHubat commit aa90e7d
Comfyui Topology Viz next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Comfyui Topology Viz this skillautomateyournetwork/netclaw | 676 | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Comfyui Skill OpenclawHuangYuChuh/ComfyUI_Skills_OpenClaw | 413 | — | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| ComfyUI Custom Node BuilderConstantineB6/comfy-pilot | 230 | — | ~897 | Automated safety check: Pass | MIT | |
| Civitaiartokun/comfyui-mcp | 803 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Setupguaardvark/guaardvark | 258 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Installer Packsartokun/comfyui-mcp | 803 | — | ~952 | Automated safety check: Pass | MIT |
HuangYuChuh/ComfyUI_Skills_OpenClaw
Run registered ComfyUI workflows through the fast comfyui-skill CLI, and use the official local Comfy MCP for live template, node, model, validation, and orchestration capabilities.
ConstantineB6/comfy-pilot
Helps an agent write ComfyUI custom nodes in Python, including wrapping an existing script, mapping data types and handling image batches.
artokun/comfyui-mcp
Discover Civitai models with the BUILT-IN downloadmodel action:"searchcivitai" and install/generate them locally.
guaardvark/guaardvark
Connect this agent to a running Guaardvark (self-hosted AI studio) and check what it can do right now.
artokun/comfyui-mcp
A skill your agent uses when installing a model family from an installer pack, or when building/deriving a new pack from an upstream installer or a workflow JSON.
artokun/comfyui-mcp
Run the ComfyUI agent locally for FREE with no subscription, no API key, and fully offline, using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama.
automateyournetwork/netclaw
Entry point for designing EVE-NG network labs: classifies the request, gathers missing requirements, proposes options and validates the resulting topology.
automateyournetwork/netclaw
Deploys Cisco ACI policy changes only behind an approved ServiceNow Change Request, capturing pre and post-change fault baselines and rolling back automatically on a fault delta.
automateyournetwork/netclaw
Runs a phased health audit of a Cisco ACI fabric through MCP tools: node status, links, tenant and policy review, faults and endpoint learning.
automateyournetwork/netclaw
Validate Arista EOS network state against ANTA's pre-built 208-test catalogue, with structured pass/fail verdicts.
automateyournetwork/netclaw
Arista CloudVision Portal (CVP) automation via REST API — device inventory, events, connectivity monitoring, tag management (4 tools).
automateyournetwork/netclaw
AWS CloudWatch monitoring — metrics, alarms, log queries, VPC flow log analysis, network performance.
Works with
Categories
Turn a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI instance — reuses the same topology model as threejs-network-viz (any of 8 topology-source integrations…. Comfyui Topology Viz is an agent skill from automateyournetwork/netclaw. Turn a network topology into one stylized, AI-generated still image via a self-hosted ComfyUI instance — reuses the same topology model as threejs-network-viz (any of 8 topology-source integrations, or a freeform description).
Comfyui Topology Viz fits situations like: the operator asks for a stylized; AI-generated image/picture/illustration of a network topology.
Run `npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a claude-code`. Or copy the skill folder (workspace/skills/comfyui-topology-viz in automateyournetwork/netclaw) into .claude/skills/comfyui-topology-viz in your project. Claude Code loads it when a task matches its description.
Run `npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a codex`. Or copy the skill folder (workspace/skills/comfyui-topology-viz in automateyournetwork/netclaw) into .agents/skills/comfyui-topology-viz in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add automateyournetwork/netclaw --skill comfyui-topology-viz -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/comfyui-topology-viz, .gemini/skills/comfyui-topology-viz, .github/skills/comfyui-topology-viz and .opencode/skills/comfyui-topology-viz in your project.
Going by SKILL.md and its folder, Comfyui Topology Viz needs Python for the scripts in its folder and the command-line tools its instructions call (npm). Our summary lists: Python 3; Node.js.
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Comfyui Topology Viz is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.9k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Comfyui Topology Viz: Comfyui Skill Openclaw (HuangYuChuh/ComfyUI_Skills_OpenClaw, 413 stars), ComfyUI Custom Node Builder (ConstantineB6/comfy-pilot, 230 stars), Civitai (artokun/comfyui-mcp, 803 stars) and Setup (guaardvark/guaardvark, 258 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
automateyournetwork (a GitHub user) maintains it in automateyournetwork/netclaw, which has 676 GitHub stars. The repository holds 120 skills in this directory. The repository was last updated on October 9, 2026.
Source: automateyournetwork/netclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.