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/m-binimran/design-pack/image-editnpx skills add m-binimran/design-pack --skill image-editgit clone --depth 1 https://github.com/m-binimran/design-packWrote 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/m-binimran/design-pack/image-edit)<a href="https://agentmods.dev/skills/m-binimran/design-pack/image-edit"><img src="https://agentmods.dev/badge/skills/m-binimran/design-pack/image-edit.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 | $0.00045 | $0.00305 |
| Opus 5 | $0.00023 | $0.00152 |
| Sonnet 5 | $0.00009 | $0.00061 |
| Haiku 4.5 | $0.00005 | $0.00030 |
Grade A, and why
image-edit 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.
What it actually says
image-edit
Non-destructive, disclosed, and licensed editing via the right connector.
Pick the connector
- Adobe Express / Firefly: background removal, generative fill/expand, object cleanup, colour adjustments.
- Nano Banana (Gemini): prompt-based edits and multi-image compositing (blend references).
(See
mcp/CONNECTORS.md.)
Process
- State the edit precisely (remove background, extend canvas to 16:9, remove the trash can, warm the tone).
- Run it through the connector; confirm the result returned.
- Check it didn't misrepresent a real subject (for product/real-estate/editorial, don't alter material facts).
- Disclose AI editing where required (the
ai/license rules), and keep the original. - Export at the right format/size/colour profile (hand to
asset-export).
Output
- The edited image (confirmed from the connector), what changed, and a disclosure/license note.
Guardrails
- Don't claim an edit happened if the connector didn't run it.
- Disclose AI alteration when it matters; don't edit away material truth in documentary/product imagery.
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 · 28 lines · 45 tokens per session scan A ae70ba6a8c33
image-edit is a skill published in the GitHub repository m-binimran/design-pack (3 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 305 once invoked, about $0.0002 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 2026-08-31.
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