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 moonlight-lupin/agent-skills --skill image-studiogit clone --depth 1 https://github.com/moonlight-lupin/agent-skillsWrote 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/moonlight-lupin/agent-skills/image-studio)<a href="https://agentmods.dev/skills/moonlight-lupin/agent-skills/image-studio"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/image-studio/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/moonlight-lupin/agent-skills/image-studio"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/image-studio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 108 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00214 | $0.06283 |
| Opus 5 | $0.00107 | $0.03141 |
| Sonnet 5 | $0.00043 | $0.01257 |
| Haiku 4.5 | $0.00021 | $0.00628 |
Grade A, and why
image-studio 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 10d 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 — 462 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Studio
Turn an idea into a finished image through three deliberate stages — brainstorm → prototype cheaply → produce the final — using fal.ai. The point of the staging is cost and control: iterate cheaply on a fast model, lock the concept with the user, then spend on a quality model only once, on the agreed image.
This skill generates files locally for the user to review and use. It never posts, publishes, or sends anything as final brand collateral.
Scope and routing
Use this skill only when all of the following are true:
- The task is generative imagery or image editing, not layout/design automation, charting, dashboarding, flowcharting, or slide/deck production.
- The user is comfortable with fal.ai egress and paid API usage.
- The local helper workflow is available or the user is asking you to prepare the prompt/brief for that workflow.
Do not use this skill for:
- Canva templates, PowerPoint decks, branded presentation layouts, data charts, dashboards, flowcharts, architecture diagrams, or process diagrams.
- Video generation.
- Confidential or sensitive image/document processing.
- Any host environment where a native image-generation/editing tool is explicitly mandated.
Three modes — choose first
The workflow depends on whether you are creating an image, changing an existing one, or cleaning up an existing one — they do not use the same steps:
- Path A · Create from scratch (no source image). The composition is unknown, so prototype cheaply to explore it, then finalise at quality — use Stage 1 → 2 → 3 below.
- Path B · Edit / overlay on an existing image (populate a room with people, restyle a photo,
add or remove an element). The composition is already fixed by the source photo, so a cheap
prototype only adds drift and artefacts that do not predict the quality result — skip it.
Brainstorm and confirm the prompt (Stage 1), then quality-edit the original directly
(Stage 3). For cost-sensitive multi-iteration work, iterate on the same-family
fal-ai/nano-banana/edit(a faithful preview) rather than on Kontext dev. The "prototype" is the agreed prompt, not an image. - Path C · Clean up / enhance an existing photo (turn an amateur/phone shot professional — fix
flare, reflections, white balance, exposure, perspective/warp, noise, clutter). Same mechanics as
Path B (no prototype; quality-edit the original in one comprehensive pass), but the intent is
faithful correction, not change — build the prompt from
references/cleanup-checklist.mdand keep every real feature exactly. Works for any subject — interiors, portraits, products, food, landscapes. One checklist-driven pass usually suffices. See the Clean-up section below.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 462 lines · 214 tokens per session scan A f579f55a3d6b
image-studio is a skill published in the GitHub repository moonlight-lupin/agent-skills (57 stars, last pushed 2d ago), licensed MIT. It adds 214 tokens to every session and 6,283 once invoked, about $0.0011 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.
Other skills, from other repositories
image
Create or optimize marketing images, social graphics, product mockups, banners, cover art, listing visuals, brand assets, image prompts, WebP files, and OG images.
video
Plan and produce video with available AI tools or programmatic frameworks. Use for video prompts, avatars, explainers, demos, templates, pipelines, and generation.
notion-infographic
Turn articles, notes, transcripts, or research into a consistent series of clean hand-drawn infographics with concise text and visual verification.
pptx
Create, inspect, extract, edit, render, and verify PowerPoint presentations with python-pptx and optional LibreOffice.
rylai-ppt
Create editable PowerPoint decks from a local JSON specification using Rylai's visual system, python-pptx, deterministic slide types, and optional rendering.
chart-image
Create publication-quality chart images from supplied data using an available plotting library, with explicit scales, labels, and visual QA.