One model workflow vs a model router
The upstream repository describes both as Agent Skills for calling the RunComfy Model API through its CLI. The practical distinction is scope: Nano Banana Edit names one endpoint, while Image Edit classifies an editing request and routes it to one of several model endpoints.
This comparison summarizes the upstream files as checked on October 16, 2026. These are documented capabilities and maintainer guidance, not SkillSignal's controlled tests or an independent image-quality ranking.
| Skill | Documented workflow | Consider it when | Evidence boundary |
|---|---|---|---|
| nano-banana-edit | Uses Google Nano Banana 2 Edit through RunComfy; the source specifies 1–20 fetchable HTTPS input images and 1–4 outputs per call. | You want one named editing route for a repeatable task or a consistently framed image batch. | Input and output limits come from the Skill file. They do not prove visual quality, identity preservation, speed, or cost. |
| image-edit | Routes by stated intent among Nano Banana Edit, GPT Image 2 Edit, Flux Kontext Pro, and Z-Image Turbo Inpaint. | You handle different kinds of edits and prefer the Agent to follow the repository's routing instructions. | The routing table is maintainer guidance; it is not an independent test that one model is best for every prompt or image. |
Which one fits your image task?
Start with nano-banana-edit for a workflow that explicitly calls for Nano Banana 2 Edit—for example, a repeatable background change or a batch where you want the same documented route. The source says inputs must be publicly fetchable HTTPS URLs; that is a technical requirement, not a recommendation to expose private images.
Consider image-edit when the work varies—for example, batch edits, text inside an image, a precise single-reference edit, or mask-based inpainting. Its README assigns these intents to different endpoints. Treat that assignment as a starting point to verify, not a guarantee that the selected model will produce the best result.
If you only need to create a new image from text, an image-editing Skill may be the wrong fit. Do not install both just because their names overlap: begin with one, test a representative non-sensitive task, and add the router only if you have a separate use case.
- Write down the edit you need: consistent batch, background change, embedded text, precise local change, or masked region.
- Choose the narrowest Skill whose documented workflow matches that task.
- Compare the result with the original and check the current account, model availability, and usage terms before making the workflow routine.
Install one Skill for Codex
Run only the command for the Skill you chose, from the project where you want to install it. These commands use project scope by default; add -g only if you intentionally want a personal install across repositories.
The upstream README lists the RunComfy CLI and a RunComfy account/login as prerequisites. Installing an Agent Skill does not install that CLI or establish that your account can call a particular model.
npx skills add agentspace-so/runcomfy-skills --skill nano-banana-edit --agent codexnpx skills add agentspace-so/runcomfy-skills --skill image-edit --agent codex- Inspect the Skill instructions and planned model route before your first run.
- Check current RunComfy access and any usage or credit terms; open-source Skill files do not mean remote model calls are free.
- Keep any API token in a secret store, not in a prompt, repository, or command history.
Protect images and understand the limits
The Nano Banana Edit Skill says its input image URLs are fetched by the RunComfy model server. Do not submit private, customer, medical, or identifiable images unless you have permission and have reviewed the provider's current data-handling terms. Check the applicable input and privacy requirements separately for other routes.
SkillSignal reviewed the linked repository documentation and install commands; it did not install either Skill, submit an image, measure latency or charges, or run a side-by-side quality test. Recheck the upstream files before use because model catalogs and instructions can change.
- Use a non-sensitive sample image for the first test.
- Keep the original and check for identity drift, text errors, artifacts, and unintended changes.
- Review rights and output accuracy before publishing or using an edited image commercially.