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 storybook-pipelinegit 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/storybook-pipeline)<a href="https://agentmods.dev/skills/hassancs91/claude-image-generation/storybook-pipeline"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/storybook-pipeline/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/storybook-pipeline"><img src="https://agentmods.dev/badge/skills/hassancs91/claude-image-generation/storybook-pipeline.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 92 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 | $0.00240 | $0.02390 |
| Opus 5 | $0.00120 | $0.01195 |
| Sonnet 5 | $0.00048 | $0.00478 |
| Haiku 4.5 | $0.00024 | $0.00239 |
Grade A, and why
storybook-pipeline 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 13d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Storybook Pipeline (Orchestrator)
The runbook for turning one English story into a finished, self-contained HTML storybook. It does no creative work itself — it dispatches the 4 component skills in order, with the right artifact paths, and locks the filename convention so every output pairs cleanly by scene index.
It exists so that in a fresh session, "make a storybook from this story" has a single entry point — no need to remember the 4 skills, their order, or the filename conventions.
When this skill applies
The user has an English story (typically in stories/) and wants the full output: scenes + images + audio + a single HTML storybook. Common phrasings:
- "run the pipeline on
stories/the-little-cloud.md" - "make a storybook from this story"
- "turn this into an illustrated storybook"
- "build the storybook end to end"
Does NOT apply to:
- Single-step requests — if they only want images, invoke
story-illustrator; only audio,story-narrator. The orchestrator is for the full chain. - Re-running after partial completion — if some artifacts exist, detect them and resume from the next missing step; don't blindly overwrite. Ask if unsure.
Pipeline order (LOCKED)
input: stories/{slug}.md
1. scene-splitter → {slug}_scenes.json
2. story-illustrator → {slug}_bible.md, {slug}_shotlist.md, {slug}_images.json
3. story-narrator → {slug}_audio/{slug}_part_NN.mp3 (+ manifest.json, optional title.mp3)
4. story-html-publisher → {slug}_story.json + {slug}.html ← the deliverable
Steps 2 and 3 both read {slug}_scenes.json and are independent — but in an interactive session run them in order so the user reviews each at its own gate.
Slug + filename convention (LOCKED)
The slug is derived from the story title or filename: lowercased, hyphenated, ASCII-safe (^[a-z0-9-]+$, max 60 chars). Every artifact shares it. All artifacts live in stories/{slug}/; the raw .md stays at stories/ (it's the trigger, not an artifact). See CLAUDE.md for the full filename table.
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.
- 13d ago First seen · 124 lines · 240 tokens per session scan A e03bc73e1dfa
storybook-pipeline is a skill published in the GitHub repository hassancs91/claude-image-generation (92 stars, last pushed 25d ago), licensed MIT. It adds 240 tokens to every session and 2,390 once invoked, about $0.0012 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.
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