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SateezgSateezg/codex-bridge/skills/edit-image/SKILL.md

edit-image

Skill248 starsChanged 3 months agoMITView on GitHub

Edit, restyle, or vary an EXISTING image file using OpenAI gpt-image-2 through the Codex CLI — change one thing and keep the rest, swap a background, recolor to a brand palette, add or fix text, or produce style-matched variants of a reference image. Use whenever the user points at an image file and asks to change, fix, restyle, clean up, or make a version of it.

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3 other projects use a version of this.

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  • Other versions3 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 3

    1. Runware/runware-skills★ 8same name
    2. celeryhq/simplified-ai★ 4same name
    3. SamurAIGPT/muapi-claude-code★ 4same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository5 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Never overwrite the source: Write to a new file; offer to replace only after the user has seen the result.

    line 49
  2. Distinctive:

    Verify by viewing: Read the output PNG with the Read tool and compare against the request before reporting done.

    line 53
  3. Very specific:

    Verify transparent corners and no colour fringe afterwards.

    line 65

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Edit an existing image (gpt-image-2 via Codex CLI)

Same wrapper as generation, plus --ref to attach the source image:

codex-imagegen "<what to change>" <output.png> --ref <source.png> [--size WxH]

The wrapper attaches the reference with codex exec -i, tells Codex to preserve everything not mentioned, and prints the absolute path of the new file. The source file is never modified — always write to a new path.

Examples

# change one thing, keep the rest
codex-imagegen "change the sky to a sunset orange, keep the building and people identical" \
  ./out/hero-sunset.png --ref ./assets/hero.png

# recolor to a brand palette
codex-imagegen "recolor to a monochrome palette of #2563EB on white, keep the exact shapes" \
  ./out/icon-blue.png --ref ./assets/icon.png

# style-matched sibling asset
codex-imagegen "a settings gear icon in exactly the style of the reference: same stroke weight, same palette, same corner radius" \
  ./out/settings.png --ref ./assets/home.png

Up to four --ref images can be passed — useful when one is the subject and the others are style references. Say in the prompt which is which.

Writing the change description

Be surgical. The model preserves what you don't mention, so name the change and then name what must survive it:

  • Good: "replace the text on the sign with 'OPEN 24/7', keep the font style, lighting and every other element identical"
  • Bad: "make it better" — produces an unrelated image

For a series of edits, chain them one at a time (each output becomes the next --ref) rather than stacking five changes into one prompt.

Rules

  1. Never overwrite the source. Write to a new file; offer to replace only after the user has seen the result. Note that Codex itself resists overwriting — the wrapper prints the path actually written, which may be a versioned sibling like out-v2.png. Use the printed path, not the one you asked for.
  2. Verify by viewing. Read the output PNG with the Read tool and compare against the request before reporting done. Regenerate with a sharper prompt if the model drifted — at most 2 retries.
  3. Use a Bash timeout of at least 300000 ms (5 minutes).
  4. For a transparent result, regenerate the subject on a flat #00FF00 background (#FF00FF if the subject is green) and strip the key with the helper Codex ships:
    python "${CODEX_HOME:-$HOME/.codex}/skills/.system/imagegen/scripts/remove_chroma_key.py" \
      --input ./keyed.png --out ./final.png --auto-key border --soft-matte \
      --transparent-threshold 12 --opaque-threshold 220 --despill
    Verify transparent corners and no colour fringe afterwards. True native transparency needs Codex's CLI fallback plus an OPENAI_API_KEY — only raise that option for hard subjects (hair, fur, glass, smoke) and let the user decide.
  5. Not for precise pixel work. Cropping, resizing, rotating, format conversion and compression are faster and lossless with ImageMagick or sips — use those directly instead of regenerating.
  6. Each edit spends the user's ChatGPT plan quota. Don't loop unprompted.

For multi-image jobs, hand the whole brief to the codex-artist subagent instead.

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