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 skills add krusemediallc/cursor-ad-agent --skill chatgpt-image-ad-arcads-mcpgit clone --depth 1 https://github.com/krusemediallc/cursor-ad-agentWrote 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/krusemediallc/cursor-ad-agent/chatgpt-image-ad-arcads-mcp)<a href="https://agentmods.dev/skills/krusemediallc/cursor-ad-agent/chatgpt-image-ad-arcads-mcp"><img src="https://agentmods.dev/badge/skills/krusemediallc/cursor-ad-agent/chatgpt-image-ad-arcads-mcp/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/krusemediallc/cursor-ad-agent/chatgpt-image-ad-arcads-mcp"><img src="https://agentmods.dev/badge/skills/krusemediallc/cursor-ad-agent/chatgpt-image-ad-arcads-mcp.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00126 | $0.02954 |
| Opus 5 | $0.00063 | $0.01477 |
| Sonnet 5 | $0.00025 | $0.00591 |
| Haiku 4.5 | $0.00013 | $0.00295 |
Grade A, and why
chatgpt-image-ad-arcads-mcp scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| `generate_image.py` + curl auth / `.env` | `arcads_generate_image_gpt` (MCP handles auth) | How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
chatgpt-image-ad (Arcads MCP)
Generate standalone Meta image-ad creatives with gpt-image-2 through the
Arcads MCP server. The image files hand off to your meta-ad-builder skill —
this skill generates images only.
This is the MCP-native version of chatgpt-image-ad. It replaces the REST
machinery — no .env, no HTTP Basic auth, no generate_image.py, no manual
presigned-upload loop, no session-folder REST calls. The Arcads MCP server handles
auth, upload, and generation.
REST chatgpt-image-ad step |
MCP replacement |
|---|---|
generate_image.py + curl auth / .env |
arcads_generate_image_gpt (MCP handles auth) |
POST /v2/images/generate model:"gpt-image-2" |
arcads_generate_image_gpt(model="gpt-image-2") |
POST /v1/file-upload/get-presigned-url + PUT (in-script) |
arcads_get_upload_url + PUT (explicit — see Uploading) |
GET /v1/assets/{id} polling loop |
arcads_watch_asset (status and URL in one call) |
--n → N parallel POSTs |
nbGenerations (1–10) in a single call |
PRODUCT_ID / session folder |
nothing — productId auto-selects |
Tools used (Arcads MCP)
| Tool | Role |
|---|---|
arcads_generate_image_gpt |
Generate the ad. model:"gpt-image-2", prompt, aspectRatio, referenceImages (≤5), nbGenerations (1–10). |
arcads_get_upload_url |
Presigned S3 URL for each local reference image. Required in remote agent clients such as Cursor. |
arcads_watch_asset |
Poll status and fetch the signed downloadUrl. Primary poll tool. |
arcads_list_products |
Resolve productId (optional — auto-selects with one product). |
arcads_generate_image_gpt parameters
| Param | Value | Notes |
|---|---|---|
prompt |
string (required) | The rewritten ad prompt (Phase 3). |
model |
"gpt-image-2" |
Locked. gpt-image-2 > gpt-image for text fidelity. |
aspectRatio |
"1:1" | "16:9" | "9:16" |
Only these three. No 4:5/2:3 on this backend — render 1:1 and crop. |
referenceImages |
array, max 5 | S3 filePaths from upload (not local paths, not asset ids). |
nbGenerations |
1–10 |
Variants in one call. Default 1; cap 5 for ad batches. |
productId |
UUID | Optional — auto-selected if only one product. |
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.
- 12d ago First seen · 164 lines · 126 tokens per session scan A 565ad46497d6
chatgpt-image-ad-arcads-mcp is a skill published in the GitHub repository krusemediallc/cursor-ad-agent (10 stars, last pushed 1mo ago), licensed MIT. It adds 126 tokens to every session and 2,954 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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