How to manage multi-brand asset packs with Picsart CLI skills

What you'll learn
What are multi-brand packs?
Common use cases
Set up multi-brand packs step by step
STEP 1: Install the CLI and create workspace
- On web: Visit picsart.com/cli → Copy install command → Paste into terminal → Run gen-ai login
- On mobile: Not applicable — multi-brand workflows require terminal access on desktop systems
STEP 2: Organize brand asset folders
Create a folder structure for each client brand:
- Create one folder per client (e.g., /brands/client-a, /brands/client-b)
- Add brand.md file with colors, fonts, logo paths, and usage rules
- Store logos, templates, and reference images in each brand folder
- Use consistent naming conventions across all client folders

STEP 3: Generate content with brand flag
Run any skill with the --brand flag to specify which client. The CLI loads that brand's assets and applies all guidelines automatically. Switch between clients by changing the flag value — no re-upload, no reconfiguration.
STEP 4: Verify brand consistency
Check that outputs match the correct brand: Not perfect? Update the brand.md file with clearer rules, or add reference images to guide the AI more precisely.
- Confirm logos and colors match the selected brand guidelines
- Check that tone and visual style align with brand identity
- Verify file naming follows your client's delivery specs
Tips for best results
💡 Use detailed brand.md files
The more specific your brand guidelines, the better the output. Include not just colors and logos, but tone of voice, imagery style, spacing rules, and examples of approved vs. rejected work.
💡 Store reusable templates per brand
Save common formats (social post, email header, ad banner) as templates in each brand folder. Reference them in your commands instead of describing layouts from scratch every time.
💡 Version-control your brand folders
Put your /brands directory in Git. When a client updates their logo or guidelines, you have a history of changes and can revert if needed.
💡 Test new brands with small batches
Before running 100 generations for a new client, test with 3-5 outputs. Make sure the skill is reading brand.md correctly and applying rules as expected.
Frequently asked questions

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