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 PicsArt/gen-ai-skills --skill caption-decorationsgit clone --depth 1 https://github.com/PicsArt/gen-ai-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/picsart/gen-ai-skills/caption-decorations)<a href="https://agentmods.dev/skills/picsart/gen-ai-skills/caption-decorations"><img src="https://agentmods.dev/badge/skills/picsart/gen-ai-skills/caption-decorations/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/picsart/gen-ai-skills/caption-decorations"><img src="https://agentmods.dev/badge/skills/picsart/gen-ai-skills/caption-decorations.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00052 | $0.02186 |
| Opus 5.5 | $0.00021 | $0.00874 |
| Sonnet 5.5 | $0.00010 | $0.00437 |
| Haiku 4.5 | $0.00005 | $0.00219 |
Grade A, and why
caption-decorations 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 today.
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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Caption decoration authoring
Choose the asset form from the behavior, not the visual appearance.
| Need | Declare | Caption row |
|---|---|---|
| Artwork generated from measured word/line geometry | type: "decoration" with a procedural shape definition |
preset: "<asset-id>" plus params |
| Arbitrary editable artwork: shapes, text, media, nested scenes, stickers | type: "scene" with a scene body |
content.kind: "scene_ref" |
| External image/video/Lottie/SVG | its ordinary media asset type | content.kind: "media" |
type: "decoration" is not a general scene container. It is the measured caption-definition language: its shape reads boxW, boxH, optional measured path, and declared params. General artwork already has the full scene language through scene_ref.
Caption-row padding, size, gap, and offset are multiples of the effective caption font em. Platform text measurement still owns x/width, optical centring, and the advance between wrapped lines. Definition-side boxW/boxH are the resulting decoration box after those row fields are applied.
Line wrapping happens at the style's wrapWidth (composition pixels) when it sets one, else at the FULL WIDTH of the composition it renders in (no margin). Either width is fixed in PIXELS, never scaled to font size, so a SMALLER font fits more characters before it wraps: shrinking the font can turn two wrapped lines into one wider one, up to that width.
Generated decoration/segment layer ids share a stem. A caption segment/decoration gets a <layer>__seg<i>__dec<d> stem, so an id containing __seg0__dec0 belongs to the first segment's first decoration. It is followed by a form suffix (e.g. __band, __stick, __bandreveal, __pillw<word>) that is not part of the contract. Select a decoration by its stem or its structure (target/place/row index), never by its full generated id.
Procedural measured preset
The asset key is the preset name; decoration.name may be omitted. Parameters are declared once and read at their actual shape sites.
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.
- today First seen · 173 lines · 52 tokens per session scan A f422ae658dc4
caption-decorations is a skill published in the GitHub repository PicsArt/gen-ai-skills (6 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 2,186 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-28.
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