Remix from library
Find an existing asset in the user's Tolstoy library and generate new on-brand variations of it. Use when the user says "make more like my best one", "clone this ad", "give me variations of that video", "remix my <asset>", or wants new creative based on something they already have in Tolstoy. Chains the Tolstoy Library MCP (find) with Tolstoy Studio (generate).From its SKILL.md
npx -y skills add GoTolstoy/agent-skills --skill remix-from-libraryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
2.4 KB, 502 tokens by cl100k_base, as published. Nobody here has run it
Remix from library
Take something the user already has in their Tolstoy library and spin new variations — using the original as a visual reference so the new creative stays on-brand.
The workflow
-
Find the source asset.
- Named or described →
search_assetswith that query. - "My recent / latest" →
list_assets. - "My favorites / starred" →
list_assetswithfavoritedOnly: true. - Be honest: the Library MCP does NOT expose performance metrics — you cannot know which asset is actually "best-performing." If the user says "my best ad," surface the most likely candidates (favorited / recent / matching their description) and confirm which one before remixing. Don't guess silently.
- Named or described →
-
Get the reference image URL. The reference must be an image:
- Image asset → its
mediaUrl. - Video asset → its
thumbnailUrl. Callget_assetfor full detail if the search/list result is thin.
- Image asset → its
-
Generate variations. Call
generate_studio_contentwith that URL inreferenceImageUrls,assetTypefor what they want (imageorvideo), anaspectRatiofor the destination, and a prompt describing the variation intent (e.g. "3 variations with different backgrounds, same product and brand feel"). Reference-to-output keeps the product/identity while letting composition vary. -
Iterate with
iterate_studio_content(samechatId) for refinements.
Example
"Clone my best serum ad and give me 3 fresh versions"
list_assets{ favoritedOnly: true }(orsearch_assets "serum ad") → show candidates, confirm which one.- Take the chosen asset's
thumbnailUrl(video) ormediaUrl(image).generate_studio_content{ assetType: "video", aspectRatio: "9:16", prompt: "3 fresh variations of this serum ad — new hooks and backgrounds, same product and brand feel", referenceImageUrls: ["<asset url>"] }
Notes
referenceImageUrlsmust be public HTTPS image URLs (library CDN URLs qualify).- This creates new content; it does not modify or replace the original asset.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.