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 danielrosehill/Claude-Image-Production-Plugin --skill ai-graphicsgit clone --depth 1 https://github.com/danielrosehill/Claude-Image-Production-PluginWrote 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/danielrosehill/claude-image-production-plugin/ai-graphics)<a href="https://agentmods.dev/skills/danielrosehill/claude-image-production-plugin/ai-graphics"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-image-production-plugin/ai-graphics/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/danielrosehill/claude-image-production-plugin/ai-graphics"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-image-production-plugin/ai-graphics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.00998 |
| Opus 5.5 | $0.00033 | $0.00399 |
| Sonnet 5.5 | $0.00016 | $0.00200 |
| Haiku 4.5 | $0.00008 | $0.00100 |
Grade A, and why
ai-graphics scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
R=$(curl -s https://queue.fal.run/<endpoint> -H "Authorization: Key $FAL_KEY" \ How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Graphics
Generate banners, hero images, illustrations, social cards, characters and README artwork. For technical diagrams use the tech-comms-diagrams plugin.
Choose the model first
- Read
references/preferred-image-models.jsonat the plugin root and match the job to ause_casesentry. - Use its
default. Usepremiumonly when the default failed on this job or the user asks. Checkstatus:provisionalmeans little evidence, so say so if it matters. - If no entry fits, or the price matters, use skill
check-model-pricing. Never choose from a bareGET https://api.fal.ai/v1/modelslisting alone: it is weighted to featured, older and expensive models. - Generate a few images, not ten. Two models on the same prompt tells you more than many tries on one.
- fal is the default backend. Use Replicate when the user asks or a model is only there.
Run it
On fal (text-to-image, edits, reference images): the queue REST API with $FAL_KEY. Submit to https://queue.fal.run/<endpoint>, poll the returned status_url until COMPLETED, then GET response_url. Use the URLs from the submit response as they are: for endpoints with a subpath (fal-ai/flux/dev) status and result live under owner/app only.
with-secrets bash -c '
R=$(curl -s https://queue.fal.run/<endpoint> -H "Authorization: Key $FAL_KEY" \
-H "Content-Type: application/json" -d @args.json)
S=$(echo "$R" | jq -r .status_url); O=$(echo "$R" | jq -r .response_url)
until [ "$(curl -s -H "Authorization: Key $FAL_KEY" "$S" | jq -r .status)" = COMPLETED ]; do sleep 3; done
curl -s -H "Authorization: Key $FAL_KEY" "$O" > result.json' # images[0].url
curl -sSL -o out.png "$(jq -r '.images[0].url' result.json)"
Set the model explicitly and pass a seed. Check the real output size: square gave 512x512 on FLUX.1 and 1024x1024 on Nano Banana. The input schema for any endpoint is at https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=<id> (the current edit models take image_urls, a list). image_urls accepts a data:image/png;base64,... URI, so a local file needs no staging. Turn off enable_prompt_expansion where it exists. Flatten transparent images onto the target background colour first. curl https://fal.run/<endpoint> (synchronous) also works for short jobs.
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.
- yesterday Changed · +5 lines 8dc4ba73d6c9
- 2d ago Changed · -27 lines · +20 tokens per session 4cdcadfd9fcf
- 13d ago Changed · -6 lines a05d17dd5886
- 16d ago Changed ccd4be69ba5b
- 2mo ago First seen · 81 lines · 62 tokens per session scan A cab81a8e1660
ai-graphics is a skill published in the GitHub repository danielrosehill/Claude-Image-Production-Plugin (21 stars, last pushed yesterday), licensed MIT. It adds 82 tokens to every session and 998 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
ai-graphics compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-graphicsdanielrosehill/Claude-Image-Production-Plugin | Skill | 21 | yesterday | MIT | A | 82 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |