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 OpenLabor/openlabor --skill animate-storygit clone --depth 1 https://github.com/OpenLabor/openlaborWrote 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/openlabor/openlabor/animate-story)<a href="https://agentmods.dev/skills/openlabor/openlabor/animate-story"><img src="https://agentmods.dev/badge/skills/openlabor/openlabor/animate-story.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.01654 |
| Opus 5 | $0.00010 | $0.00827 |
| Sonnet 5 | $0.00004 | $0.00331 |
| Haiku 4.5 | $0.00002 | $0.00165 |
Grade A, and why
Animate Story 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 8d 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Animate Story
Turn photos and ideas into anime-style visual stories — generate scene-by-scene illustrated narratives.
You have access to image generation through the OpenLabor API.
How to Generate Images
use images GENERATE '{"prompt":"...","model":"flux-schnell","aspect_ratio":"9:16","num_images":"1"}'
Styles
The same pipeline supports multiple visual styles. Always ask the user which style they want, or default to anime.
| Style | Prompt Suffix |
|---|---|
| Anime/Manga | anime style, manga aesthetic, vibrant colors, dramatic lighting, studio quality |
| Ghibli | studio ghibli style, soft watercolor, whimsical, warm lighting, hand-painted feel, nostalgic |
| Comic Book | comic book style, bold ink outlines, halftone dots, dynamic panels, superhero aesthetic, vivid colors |
| Cyberpunk | cyberpunk style, neon lights, rain-soaked streets, holographic UI, dark futuristic, blade runner aesthetic |
| Watercolor | watercolor painting style, soft edges, flowing colors, artistic brushstrokes, delicate, dreamy |
| Pixel Art | pixel art style, 16-bit retro, clean pixels, limited color palette, nostalgic game aesthetic |
Pipeline
Step 1: Story Input
The user provides either:
- A photo of themselves or a scene (to be anime-fied)
- A text description of a story they want illustrated
- A topic/theme ("my morning routine as anime", "startup founder origin story")
Step 2: Scene Breakdown
Break the story into 5-8 scenes. For each scene define:
- Scene number and description (what's happening)
- Type: "anime" (AI-generated) or "real" (user's original photo)
- Image prompt for anime scenes
- Caption/text overlay (short, punchy text for the scene)
- Mood (epic, chill, romantic, dark, funny)
Example breakdown:
Scene 1: [anime] Hook — dramatic wide shot establishing the world
Scene 2: [real] User's actual photo — the "real me"
Scene 3: [anime] The struggle — character facing a challenge
Scene 4: [anime] The breakthrough moment
Scene 5: [anime] The transformation — before/after contrast
Scene 6: [real] User's photo again — "back to reality"
Scene 7: [anime] The vision — where they're heading
Scene 8: [anime] CTA scene — bold text with call to action
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.
- 8d ago First seen · 179 lines · 20 tokens per session scan A 7b79a2a75db1
Animate Story is a skill published in the GitHub repository OpenLabor/openlabor (4 stars, last pushed 7d ago), licensed MIT. It adds 20 tokens to every session and 1,654 once invoked, about $0.0001 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 2026-08-31.
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