Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/peteromallet/VibeComfynpx agentmods add skills/peteromallet/vibecomfy/run-comfy-workflowWrote 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/peteromallet/vibecomfy/run-comfy-workflow)<a href="https://agentmods.dev/skills/peteromallet/vibecomfy/run-comfy-workflow"><img src="https://agentmods.dev/badge/skills/peteromallet/vibecomfy/run-comfy-workflow/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/peteromallet/vibecomfy/run-comfy-workflow"><img src="https://agentmods.dev/badge/skills/peteromallet/vibecomfy/run-comfy-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00066 | $0.01624 |
| Opus 5.5 | $0.00026 | $0.00650 |
| Sonnet 5.5 | $0.00013 | $0.00325 |
| Haiku 4.5 | $0.00007 | $0.00162 |
Grade A, and why
run-comfy-workflow 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 1mo 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run Comfy Workflow
Use this for execution. If the graph must change first, use edit-comfy-workflow. If ComfyUI or paths are not configured, use vibecomfy-setup. If a run fails, use debug-comfy-workflow.
Preflight
vibecomfy inspect <workflow>
vibecomfy validate <workflow>
vibecomfy doctor <workflow> --json
For raw JSON or a selected Hivemind revision, use the one importer first; run the resulting local bundle:
vibecomfy import <workflow.json-or-hivemind-reference>
vibecomfy validate workflows/<name> --json
vibecomfy run workflows/<name> --runtime embedded
Embedded Runtime
@python_node and source capsules execute through the existing ordinary
vibecomfy.exec node. They run in process with the selected ComfyUI worker's
files, imports, network, credentials, and GPU privileges; there is no reliable
timeout or sandbox. Snapshot capsules are materialized in a digest-qualified
cache, while installed entrypoints use their normal package namespace. A
worker dependency check happens before source import.
Use embedded when local ComfyUI is discoverable in the active environment:
vibecomfy run <workflow.py> --runtime embedded
vibecomfy run image/z_image --ready --runtime embedded
Prompt/seed/steps CLI overrides only work when the workflow exposes matching public inputs:
vibecomfy run image/z_image --ready --runtime embedded --prompt "..." --seed 7 --steps 20
Use dependency helpers only when the user wants VibeComfy to prepare local runtime assets:
vibecomfy run <workflow.py> --runtime embedded --ensure-packs --ensure-models
--ensure-packs is embedded-only.
Canonical dependency repair loop
For a local Python workflow, run reads the authored MODELS /
ModelAsset and READY_METADATA.requirements.custom_node_refs surfaces before
compilation. Missing model URLs, repository URLs, unsafe destinations,
unsupported dynamic metadata, and root or nested node classes that are not
core, explicitly listed in a ref's classes/class_set, or covered by one
unambiguous local pack catalog are reported together. The run stops with:
"Run blocked: dependencies unresolved. Nothing downloaded, installed,
restarted, compiled, or queued." Common literal placeholders are written back
to the same workflow.py; rerunning is idempotent.
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.
- 1mo ago Changed · +52 lines 2169bac61a34
- 1mo ago Changed · +8 lines e05d69bd4470
- 1mo ago Changed · -1 lines 53b2da440b6b
- 1mo ago First seen · 96 lines · 66 tokens per session scan A 715fa7cf6976
run-comfy-workflow is a skill published in the GitHub repository peteromallet/VibeComfy (152 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 1,624 once invoked, about $0.0003 per session on Opus 5.5. 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.
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