image-edit

仓库: agentspace-so/runcomfy-agent-skills
安装量: 106.3K
排名: #124

安装

npx skills add https://github.com/agentspace-so/runcomfy-agent-skills --skill image-edit
Image Edit — Pro Pack on RunComfy
runcomfy.com
·
Nano Banana Edit
·
GPT Image 2 Edit
·
Flux Kontext
·
Z-Image Inpaint
·
GitHub
Image edit, intent-routed.
This skill doesn't lock you to one model — it picks the right edit model in the RunComfy catalog based on what the user actually wants: batch identity-preservation, multilingual text rewrite, single-shot precise edit, or mask-driven region replacement.
npx skills
add
agentspace-so/runcomfy-skills
--skill
image-edit
-g
Pick the right model for the user's intent
User intent
Model
Why
Batch edit 1–20 images consistently (SKU gallery, A/B variants)
Nano Banana Edit
Up to 20 input images per call; locked aspect/resolution for series
Swap background, preserve subject identity
Nano Banana Edit
Strong identity preservation under "keep X unchanged" prompts
Localized object removal / addition with spatial language ("the left object", "upper-right corner")
Nano Banana Edit
Honors directional spatial scope
Multilingual / non-Latin in-image text rewrite (Japanese kana, Cyrillic, Arabic)
GPT Image 2 Edit
Strongest in class for multilingual typography
Multi-reference composition (subject from img1, scene from img2, palette from img3)
GPT Image 2 Edit
Numbered refs route cues correctly
Layout-precise repositioning ("move headline from top-right to bottom-center")
GPT Image 2 Edit
Directional language honored at layout level
Identity preservation across translated headline variants
GPT Image 2 Edit
Same source asset → many language variants, identity stable
Single-shot precise local edit ("she's now holding an orange umbrella")
Flux Kontext Pro
Single-ref single-instruction, high-fidelity preservation
Mask-driven object removal (cables, watermarks, distractions)
Z-Image Turbo Inpaint
Mask-required, strength-tunable, edge-consistent
Mask-driven region replacement (full background swap with mask)
Z-Image Turbo Inpaint
High strength + clean mask = clean replacement
Default if unspecified
Nano Banana Edit
Most flexible, supports both single and batch
The agent reads this table, classifies the user's intent, and picks the matching subsection below.
Prerequisites
RunComfy CLI
—
npm i -g @runcomfy/cli
RunComfy account
—
runcomfy login
.
CI / containers
— set
RUNCOMFY_TOKEN=
.
Route 1: Nano Banana Edit — default for general edit + batch
Model
:
google/nano-banana-2/edit
Schema
Field
Type
Required
Default
Notes
prompt
string
yes
—
Lead with preservation goals, end with the change.
image_urls
array
yes
—
1–20
publicly-fetchable HTTPS URLs.
number_of_images
int
no
1
1–4 outputs per call.
aspect_ratio
enum
no
auto
auto
follows input; lock for batch consistency.
resolution
enum
no
1K
0.5K
/
1K
/
2K
/
4K
.
output_format
enum
no
png
png
/
jpeg
/
webp
.
seed
int
no
—
Reproducibility.
enable_web_search
bool
no
false
Web-grounded edits (extra latency).
Invoke
runcomfy run google/nano-banana-2/edit
\
--input
'{
"prompt": "Keep the subject identity, pose, and clothing unchanged. Convert the background into a rainy neon cyberpunk street.",
"image_urls": ["https://.../portrait.jpg"]
}'
\
--output-dir
<
absolute/path
>
Batch (lock aspect + resolution):
runcomfy run google/nano-banana-2/edit
\
--input
'{
"prompt": "Replace the watermark in the bottom-right with the text \"AURA\" in clean white sans-serif. Keep everything else exactly as in the input.",
"image_urls": ["https://.../sku-1.jpg", "https://.../sku-2.jpg", "https://.../sku-3.jpg"],
"aspect_ratio": "1:1",
"resolution": "1K"
}'
\
--output-dir
<
absolute/path
>
Prompting tips
Preservation first
:
"Keep [identity / pose / brand / framing] unchanged."
Then state the change.
Spatial scope
"background only", "the left object", "upper-right quadrant" — concrete locations honored.
Batch consistency
lock
aspect_ratio
and
resolution
across the batch.
Iterate small
split compound edits into multiple shorter passes.
Route 2: GPT Image 2 Edit — multilingual text + multi-ref composition
Model
:
openai/gpt-image-2/edit
Schema
Field
Type
Required
Default
Notes
prompt
string
yes
—
Edit instruction; lead with preservation.
images
string[]
yes
—
Up to 10
HTTPS URLs. First is primary; rest are auxiliary.
size
enum
no
auto
auto
,
1024_1024
,
1024_1536
,
1536_1024
.
Only these.
Invoke
Multilingual text rewrite:
runcomfy run openai/gpt-image-2/edit
\
--input
'{
"prompt": "Keep the photograph, layout, and brand mark exactly as in the input. Replace only the in-image headline. The new headline reads \"今日のおすすめ\" in bold Japanese kana, same position and font weight.",
"images": ["https://.../poster-en.jpg"]
}'
\
--output-dir
<
absolute/path
>
Multi-ref composition:
runcomfy run openai/gpt-image-2/edit
\
--input
'{
"prompt": "Compose subject from image 1 into the room from image 2. Match the lighting and color palette of image 2. Keep image 1 subject identity unchanged.",
"images": ["https://.../subject.jpg", "https://.../room.jpg"]
}'
\
--output-dir
<
absolute/path
>
Prompting tips
Quote in-image text exactly.
Name the script for non-Latin:
"Japanese kana"
,
"Cyrillic"
,
"Arabic right-to-left"
.
Number multi-refs
:
"subject from image 1, lighting from image 2"
.
Directional layout language
:
"move the headline from top-right to bottom-center"
,
"replace the watermark in the bottom-right"
.
size: "auto"
preserves input ratio — recommended unless the edit changes framing.
Route 3: Flux Kontext Pro — single-shot precise local edit
Model
:
blackforestlabs/flux-1-kontext/pro/edit
Schema (minimal)
Field
Type
Required
Notes
prompt
string
yes
One declarative edit instruction.
image
string
yes
Single
source image URL.
aspect_ratio
enum
no
Pick from supported W:H values.
seed
int
no
Reproducibility.
Single image only — no array. For multi-image flows, use Route 1 (Nano Banana Edit).
Invoke
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
>
Prompting tips
One declarative instruction.
"She is now holding an orange umbrella and smiling" — imperative, single change.
Preservation first.
Lead with
"Keep [unchanged elements]"
then state the change.
Iterate small.
Compound edits drift on a single pass; split into sequential passes.
Route 4: Z-Image Turbo Inpaint — mask-driven precise region edit
Model
:
tongyi-mai/z-image/turbo/inpainting
Schema
Field
Type
Required
Notes
prompt
string
yes
What to fill / replace; preservation constraints for the unmasked surround.
image
string
yes
Source image URL.
mask_image
string
yes
Grayscale mask URL
(white = inpaint, black = preserve).
strength
float
no
0.3–0.6 retouching, 0.7–1.0 full replacement.
control_scale
float
no
0.6–0.9 typical.
aspect_ratio
enum
no
W:H output ratio.
seed
int
no
Reproducibility.
Invoke
Object removal (low strength):
runcomfy run tongyi-mai/z-image/turbo/inpainting
\
--input
'{
"prompt": "Remove overhead cables; preserve rooflines and sky gradient; thin clean sky.",
"image": "https://.../street.jpg",
"mask_image": "https://.../cables-mask.png",
"strength": 0.5,
"control_scale": 0.8
}'
\
--output-dir
<
absolute/path
>
Region replacement (high strength):
runcomfy run tongyi-mai/z-image/turbo/inpainting
\
--input
'{
"prompt": "Replace busy backdrop with smooth light gray studio paper; mask background only.",
"image": "https://.../product.jpg",
"mask_image": "https://.../bg-mask.png",
"strength": 0.9
}'
\
--output-dir
<
absolute/path
>
Prompting tips
A mask URL is required
— grayscale, white = inpaint region, black = preserve. Slight blur on mask edges (1–3px) blends better than sharp binary.
Strength by intent
:
0.3–0.5
for retouching / cleanup,
0.6–0.7
for object replacement with style match,
0.8–1.0
for full-region replacement.
Name what stays outside the mask
in the prompt:
"preserve rooflines and sky gradient"
,
"match brick pattern and mortar tone"
.
Spatial labels still help
even though the mask defines the region:
"the left shelf"
,
"upper-right quadrant"
.
Limitations
Each route inherits its model's limits.
Nano Banana: 1–20 inputs, 1–4 outputs. GPT Image 2 Edit: up to 10 refs, 4 fixed sizes. Flux Kontext: single ref. Z-Image Inpaint: mask required.
No multi-route blending.
This skill picks one model per call.
Brand-specific overrides
— if the user named a specific model, route to the corresponding brand skill (
gpt-image-edit
,
flux-kontext
,
nano-banana-edit
) for fuller treatment.
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 picks one of Nano Banana Edit / GPT Image 2 Edit / Flux Kontext Pro / Z-Image Turbo Inpaint based on user intent and invokes
runcomfy run
with the matching JSON body. The CLI POSTs to the Model API, 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 login
writes the API token to
~/.config/runcomfy/token.json
with mode 0600 (owner-only read/write). Set
RUNCOMFY_TOKEN
env 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.
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