Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/sateezg/codex-bridge/edit-imagenpx skills add Sateezg/codex-bridge --skill edit-imagegit clone --depth 1 https://github.com/Sateezg/codex-bridgeWrote 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/sateezg/codex-bridge/edit-image)<a href="https://agentmods.dev/skills/sateezg/codex-bridge/edit-image"><img src="https://agentmods.dev/badge/skills/sateezg/codex-bridge/edit-image.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00090 | $0.00902 |
| Opus 5 | $0.00045 | $0.00451 |
| Sonnet 5 | $0.00018 | $0.00180 |
| Haiku 4.5 | $0.00009 | $0.00090 |
Grade A, and why
edit-image 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 4d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- 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. - 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.
- Use a Bash timeout of at least 300000 ms (5 minutes).
- For a transparent result, regenerate the subject on a flat
#00FF00background (#FF00FFif the subject is green) and strip the key with the helper Codex ships:
Verify transparent corners and no colour fringe afterwards. True native transparency needs Codex's CLI fallback plus anpython "${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 --despillOPENAI_API_KEY— only raise that option for hard subjects (hair, fur, glass, smoke) and let the user decide. - 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. - Each edit spends the user's ChatGPT plan quota. Don't loop unprompted.
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.
- 4d ago First seen · 74 lines · 90 tokens per session scan A 21ac926bdbd6
edit-image is a skill published in the GitHub repository Sateezg/codex-bridge (253 stars, last pushed 24d ago), licensed MIT. It adds 90 tokens to every session and 902 once invoked, about $0.0005 per session on Opus 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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