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 hassancs91/claude-image-generation --skill scene-splittergit clone --depth 1 https://github.com/hassancs91/claude-image-generationWrote 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/hassancs91/claude-image-generation/scene-splitter)<a href="https://agentmods.dev/skills/hassancs91/claude-image-generation/scene-splitter"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/scene-splitter/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/hassancs91/claude-image-generation/scene-splitter"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/scene-splitter.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 | $0.00209 | $0.02267 |
| Opus 5 | $0.00105 | $0.01133 |
| Sonnet 5 | $0.00042 | $0.00453 |
| Haiku 4.5 | $0.00021 | $0.00227 |
Grade A, and why
scene-splitter 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scene Splitter
Takes a plain English story and produces a numbered list of scenes — each scene being one moment that gets exactly one illustration and one narration clip downstream.
This is the upstream spine of the AI Storybook pipeline. Splitting once here and feeding both the illustrator and the narrator from the same {slug}_scenes.json keeps everything in lockstep: image N pairs with audio N pairs with paragraph N. No drift, no negotiation between skills.
When this skill applies
The user has an English story and wants to prepare it for the illustration + narration pipeline. Common phrasings: "split this into scenes", "break this into pages", "prepare this story for the storybook", "make scenes for illustration".
The skill does NOT apply to:
- Stories that need only narration OR only images standalone (the illustrator and narrator can split on their own when used independently)
- Non-narrative content (essays, instructions, lists)
Architectural rule: one scene = one moment = one image = one narration clip
A scene is a single moment that fits one illustration. Operationally, a new scene starts at any of:
- Action transition — a different action happens
- Scene change — a different location or a significant time jump
- Emotional turn — joy → fear, calm → urgency, doubt → resolve
- Character entry/exit — someone new appears or leaves the moment
- Dialogue beat — a meaningful line of speech that deserves its own picture
Scenes are deliberately short and many. The storybook player renders one scene at a time, and the text MUST fit on a phone screen without scrolling. That drives the hard length cap below.
Reading level + length cap (beginner default)
This pipeline targets beginner readers. The cap is screen-fit-driven, not API-driven:
| Level | Per-scene hard cap | Target scene count |
|---|---|---|
| beginner (default) | 240 characters | 8–12 scenes |
The cap is the number of characters in a single scene's text. Keep most scenes well under it (~120–180 chars reads best on a phone). To scale this pipeline up for longer/harder stories, raise the cap and the target count here — nothing downstream needs to change.
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 · 145 lines · 209 tokens per session scan A ddcd05cd290d
scene-splitter is a skill published in the GitHub repository hassancs91/claude-image-generation (91 stars, last pushed 23d ago), licensed MIT. It adds 209 tokens to every session and 2,267 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
imagegen
Use when the user asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (${SELENESKILLROOT}/scripts/imagegen.py) and require…
sora
Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI’s video API using the bundled CLI (${SELENESKILLROOT}/scripts/sora.py), including requests like “generate AI video,” “Sora,” “video remix,” “download video/thumbnail/spritesheet,” and batch video generation; requires…
speech
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (${SELENESKILLROOT}/scripts/texttospeech.py) with built-in voices and require OPENAIAPIKEY for live calls. Custom voice creation is out of scope.
app-mockup
Create deterministic browser, tablet, laptop, and phone mockups from real screenshots via the local TypeScript renderer in this plugin. Use for marketing visuals, store screenshots, and framed UI previews without ML image generation.
transcribe
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
dig-for-discogs
Use DIG's read-only Discogs workflows to search the catalogue or an authenticated collection, inspect releases and masters, compare pressings, rank sonic/collector/value evidence, summarize collection taste, inspect an own wantlist, and request collection-aware recommendations. Trigger for Discogs release IDs…