Summary
Three ways to turn text into images through Picsart's gen-ai CLI, consolidated into one skill with mode references. You read a paragraph and need an inline visual, you use single mode. You have a full blog draft, you use article-set mode for hero plus supporting images. You need an OG image from a URL, there's a mode for that too. The skill pushes you to extract signals first instead of throwing raw text at the generator, which matters because literal interpretations look dead. Each mode has its own prompt templates and aspect ratio guidance. If you're already using Picsart's CLI for other work, this gives you a clean entry point for content illustration without hunting through separate skills.
Install to Claude Code
npx -y skills add PicsArt/gen-ai-skills --skill text-to-visual --agent claude-codeInstalls into .claude/skills of the current project.
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SKILL.mdView on GitHub
Text to Visual
A single skill that covers every "given text, produce a matching image" workflow Picsart's gen-ai CLI supports. Use when the user has any kind of written content — a paragraph, a blog draft, a URL — and needs visuals generated from it. Replaces three narrower skills with one entry point and three mode references.
Input: text (paragraph, article, or URL). Output: one or more images matched to the text's tone, topic, and target placement.
When to Use
| Mode | Trigger phrases | Reference |
|---|---|---|
| single | "match a visual to this paragraph", "inline image for this section", "one visual for this content" | references/modes/single.md |
| article-set | "illustrate this blog post", "hero + inline visuals for an article", "full visual set for a draft" | references/modes/article-set.md |
| og | "OG image for this URL", "open graph preview", "Twitter card image", "dynamic meta image" | references/modes/og.md |
If the user wants product photos transformed, that's product-photo-studio. If they want video, that's gen-ai-use.
Prerequisites
Picsart gen-ai CLI installed and authenticated:
curl -fsSL https://picsart.com/gen-ai-cli/install.sh | bash
gen-ai login
gen-ai whoami
Per-mode setup (caching, serverless endpoints, font choices) is documented inside each mode reference.
How to Run
- Identify the mode from the user's request using the table in When to Use.
- Load the corresponding mode reference:
Readreferences/modes/<mode>.md. - Follow the procedure described there — extract text signals, build prompt, generate.
- Return to this SKILL.md only when switching modes mid-task.
Quick Reference
# Single image from a prompt
gen-ai generate --model <model> --prompt "<derived from text>"
# Estimate cost first
gen-ai pricing --model <model> --count <N>
# Browse available models
gen-ai models
Prompt-construction patterns (how to derive a prompt from a paragraph, an article, or a URL's metadata) live in the individual mode references.
Procedure
Shared outer loop:
- Extract signals — pull subject, tone, palette hints, and target dimensions from the input text.
- Build prompt — translate signals into a
gen-aiprompt; each mode has its own template. - Estimate —
gen-ai pricingbefore committing for multi-image runs. - Generate — invoke
gen-ai generate. Stream progress. - Place — drop into the right slot: PDP, blog frontmatter, OG meta tag, social variant.
Pitfalls
- Don't generate from raw text. Always extract signals first; raw paragraphs produce literal, lifeless images.
- Match aspect ratio to placement. OG = 1200×630, blog hero = 16:9, social = varies.
- Cache OG images. Don't regenerate on every page view — see
references/modes/og.md. - Mode-specific pitfalls live inside the individual mode references.
Verification
# Confirm output exists and matches expected dimensions
gen-ai inspect outputs/<run>/<image>.png
# Spot-check the visual matches the source text by re-reading both side by side
See also
product-photo-studio— transform existing product photosgen-ai-use— foundational gen-ai CLI reference
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