flux-kontext
agentspace-so/runcomfy-agent-skills
Edit images precisely with Flux 1 Kontext Pro via RunComfy CLI — single-reference local edits with strong prompt control
What is flux-kontext?
flux-kontext installs prompting patterns and CLI wiring for Black Forest Labs' Flux 1 Kontext Pro image-edit model, accessed through the RunComfy Model API. It handles single-reference local image edits — changing specific elements while preserving identity, pose, branding, or framing — and includes documented anti-patterns, routing guidance to sibling models, and exit code reference.
- Runs Flux 1 Kontext Pro image edits via `runcomfy run blackforestlabs/flux-1-kontext/pro/edit`
- Accepts a single source image URL and a declarative edit prompt
- Supports optional aspect_ratio and seed fields for reproducible variants
- Bundles verified prompting patterns (preservation-led, single-instruction) for sharper output
- Routes to sibling models (Nano Banana Edit, GPT Image 2, Flux 2 Klein) when Kontext is the wrong fit
- Downloads generated outputs to a local directory specified by --output-dir
How to install flux-kontext
npx skills add https://github.com/agentspace-so/runcomfy-agent-skills --skill flux-kontext- Node.js (to run npx skills add)
- RunComfy CLI: `npm i -g @runcomfy/cli`
- RunComfy account with `runcomfy login` (browser device-code flow)
- For CI/containers: set `RUNCOMFY_TOKEN=<token>` environment variable
- Source image must be publicly fetchable via HTTPS URL
How to use flux-kontext
- 1.Install the skill: `npx skills add https://github.com/agentspace-so/runcomfy-agent-skills --skill flux-kontext`
- 2.Authenticate: run `runcomfy login` or set `RUNCOMFY_TOKEN` in your environment
- 3.Prepare a publicly accessible HTTPS URL for your source image
- 4.Write a single declarative edit prompt; lead with preservation instructions (e.g., 'Keep face and pose unchanged.')
- 5.Run: `runcomfy run blackforestlabs/flux-1-kontext/pro/edit --input '{"prompt":"...","image":"https://..."}' --output-dir <absolute/path>`
- 6.Add `"seed": 42` to the input JSON for reproducible variant comparisons
- 7.If the edit drifts, split compound changes into sequential single-instruction passes
- 8.Check exit codes (0=success, 65=bad input, 75=retry, 77=auth) for troubleshooting
Use cases
- Precise local edits: add or swap a single object while preserving everything else
- Brand asset updates: replace label text or colors with identity preserved
- Portrait or product photo micro-edits with high source fidelity
- Iterative single-image variant generation using a fixed seed
- Sequential multi-pass edits where compound prompts would cause drift
- Developers building image-editing pipelines with coding agents like Claude Code or Cursor
- Designers needing scriptable, reproducible local image edits
- Product teams doing brand-asset text or color swaps at scale
- Anyone explicitly requesting Flux Kontext / BFL Kontext in their workflow
- CI/CD pipelines requiring token-based (non-interactive) image editing
flux-kontext FAQ
Use Nano Banana Edit when you need to edit multiple images in a batch (1–20 images) or when your workflow requires multi-image reference inputs. Flux Kontext only accepts a single source image.
Flux Kontext handles quoted brand text swaps reasonably well with preservation-led prompts, but for multilingual or complex embedded text editing, GPT Image 2 edit is recommended.
Kontext is optimized for single declarative instructions. Prompts with multiple simultaneous changes (change A and add B and remove C) cause drift. Split into sequential single-instruction passes instead.
Set the `RUNCOMFY_TOKEN=<token>` environment variable. The CLI will use this token instead of reading from `~/.config/runcomfy/token.json`, bypassing the browser login flow entirely.
Image URLs are fetched by the RunComfy model server, not by the CLI on your local machine. Only `model-api.runcomfy.net` and `*.runcomfy.net`/`*.runcomfy.com` are contacted; there is no telemetry.
Full instructions (SKILL.md)
Source of truth, from agentspace-so/runcomfy-agent-skills.
name: flux-kontext
displayName: "Flux Kontext Pro — Pro Pack on RunComfy"
description: >
Edit images with Flux 1 Kontext Pro (Black Forest Labs' precise local
image-edit model) on RunComfy — bundled with the model's documented
prompting patterns so the skill gets sharper output than naive
prompting against the same model. Documents Flux Kontext's strengths
(single-reference precise local edits, strong prompt control,
consistent high-fidelity outputs), the schema (single image + prompt),
and when to route to Nano Banana Edit / GPT Image 2 edit / Flux 2
Klein instead. Calls
runcomfy run blackforestlabs/flux-1-kontext/pro/edit through the
local RunComfy CLI. Triggers on "flux kontext", "flux-kontext",
"flux 1 kontext", "kontext", "BFL kontext", or any explicit ask to
edit with this model.
homepage: https://www.runcomfy.com
license: MIT
Flux Kontext Pro — Pro Pack on RunComfy
runcomfy.com · Model page · GitHub
Black Forest Labs' Flux 1 Kontext Pro — single-reference precise local image edit — hosted on the RunComfy Model API. Strong prompt control, consistent outputs, high fidelity.
npx skills add agentspace-so/runcomfy-skills --skill flux-kontext -g
When to pick this model (vs siblings)
| You want | Use |
|---|---|
| Single-image precise local edit ("she's now holding X") | Flux Kontext |
| High-fidelity preservation of source identity | Flux Kontext |
| Batch edits across 1–20 images | Nano Banana Edit |
| Edit multilingual / embedded text in image | GPT Image 2 edit |
| Generate from scratch, no source image | Flux 2 Klein |
If the user said "Flux Kontext" / "kontext" / "BFL Kontext" explicitly, route here regardless.
Prerequisites
- RunComfy CLI —
npm i -g @runcomfy/cli - RunComfy account —
runcomfy loginopens a browser device-code flow. - CI / containers — set
RUNCOMFY_TOKEN=<token>instead ofruncomfy login.
Endpoints + input schema
blackforestlabs/flux-1-kontext/pro/edit
| Field | Type | Required | Default | Notes |
|---|---|---|---|---|
prompt | string | yes | — | Single declarative edit instruction. |
image | string | yes | — | Single source image URL (publicly fetchable HTTPS). |
aspect_ratio | enum | no | (input) | Pick from supported W:H options on the model page. |
seed | int | no | — | Reuse for variant comparisons. |
The schema is intentionally minimal — Kontext leans on prompt + single ref. For multi-image or web-grounded edits, route to Nano Banana Edit.
How to invoke
Default — local edit, preserve everything else:
runcomfy run blackforestlabs/flux-1-kontext/pro/edit \
--input '{
"prompt": "Keep the person'\''s face, pose, and clothing unchanged. Add an orange umbrella in her left hand and a slight smile.",
"image": "https://.../portrait.jpg"
}' \
--output-dir <absolute/path>
With seed for reproducible variant series:
runcomfy run blackforestlabs/flux-1-kontext/pro/edit \
--input '{
"prompt": "Keep the bottle, label, and lighting unchanged. Replace the brand text on the label from \"ALPHA\" to \"AURA\".",
"image": "https://.../bottle.jpg",
"seed": 42
}' \
--output-dir <absolute/path>
Prompting — what actually works
One declarative instruction. Kontext shines on prompts shaped like the docs example: "She is now holding an orange umbrella and smiling". Imperative mood, single change.
Preservation first. Lead with "Keep [identity / pose / framing / brand] unchanged." Then the change. Models honor what's stated up front.
Single ref only — pick the right one. No multi-image fanout here. If you have multiple references, decide which is primary and pass that one. For multi-image flows, route to Nano Banana Edit.
Iterate on small changes. If Kontext drifts, split a compound edit into sequential single-instruction passes (pass 1: change background, pass 2: change clothing).
Aspect ratio — pick from the supported enum. Out-of-list values 422 or crop.
Anti-patterns:
- Compound prompts ("change A and add B and remove C") → drift.
- Trying to fan out to multiple source images → wrong model (use Nano Banana Edit).
- Prompts written in passive voice → less reliable.
- Asking for novel composition without a source image → wrong model (use Flux 2 Klein t2i).
Where it shines
| Use case | Why Flux Kontext |
|---|---|
| Single-shot precise local edit | Specifically designed for this; high fidelity |
| Preserve source identity through targeted change | Strong preservation under explicit instruction |
| Brand-asset text or color swap | Quoted text + preservation lead-in works well |
| Quick iteration on one image | Short prompts + single ref = fast result loop |
Sample prompts (verified to produce strong results)
Page example:
She is now holding an orange umbrella and smiling
Preservation-led brand edit:
Keep the bottle silhouette, table, and lighting exactly as in the input.
Replace only the brand text on the label, from "ALPHA" to "AURA".
Same font weight, white on black, centered.
Compositional micro-edit:
Keep the person's face, pose, and clothing unchanged. Add a leather
shoulder bag, dark brown, hanging on the right shoulder.
Limitations
- Single source image only. For multi-image flows, use Nano Banana Edit (1–20).
- Public RunComfy docs are minimal — schema fields beyond prompt + image + aspect_ratio + seed may exist; check the model page for the latest field list.
- Compound prompts drift — split into sequential passes.
- For multilingual / embedded text editing, GPT Image 2 edit usually wins.
Exit codes
| code | meaning |
|---|---|
| 0 | success |
| 64 | bad CLI args |
| 65 | bad input JSON / schema mismatch |
| 69 | upstream 5xx |
| 75 | retryable: timeout / 429 |
| 77 | not signed in or token rejected |
Full reference: docs.runcomfy.com/cli/troubleshooting.
How it works
The skill invokes runcomfy run blackforestlabs/flux-1-kontext/pro/edit with a JSON body matching the schema. The CLI POSTs to https://model-api.runcomfy.net/v1/models/blackforestlabs/flux-1-kontext/pro/edit, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.
Security & Privacy
- Token storage:
runcomfy loginwrites the API token to~/.config/runcomfy/token.jsonwith mode 0600 (owner-only read/write). SetRUNCOMFY_TOKENenv var to bypass the file entirely in CI / containers. - Input boundary: the user prompt is passed as a JSON string to the CLI via
--input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content. - Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
- Outbound endpoints: only
model-api.runcomfy.net(request submission) and*.runcomfy.net/*.runcomfy.com(download whitelist for generated outputs). No telemetry, no callbacks. - Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.
Related skills
More from agentspace-so/runcomfy-agent-skills and the wider catalog.
video-edit
>
image-to-video
>
nano-banana-2
>
image-edit
>
nano-banana-edit
>
wan-2-7
>