Agent skill

Scenario Ad Variants

by scenario-labs in scenario-labs/skills

A skill your agent uses when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants.

MITAuto-check passedMedia & Creative

Install Scenario Ad Variants

skills CLI
$ npx skills add scenario-labs/skills --skill scenario-ad-variants -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install scenario-labs/skills scenario-ad-variants --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-ad-variants .claude/skills/scenario-ad-variants && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scenario-ad-variants
GitHub stars
946
Token cost
~2.1k tokens
SKILL.md length
1,098 words
Files
1
Skills in repo
146
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants.

  • Works in 6 steps: asset_get the source, then inspect it.… → Record variants A, B and C with the same… → Follow scenario-video-assembly:… → …
  • Making multiple independent ad
  • SKILL.md covers Overview, Quick reference, Source and variant records and Worked example: three hook…, plus 1 more section
  • Calls npx

What it does

Scenario Ad Variants is an agent skill from scenario-labs/skills. Use when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Also for revising one variant or resuming a partially completed batch. Not for a new commercial from a still image, ordinary single-clip grading, or automatic Cartesian combinations.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.

When your agent uses it

  • Making multiple independent ad
  • Campaign edits from existing footage with Scenario: hook
  • Targeted visual variants

Example prompts

  • “/scenario-ad-variants”

Requirements

  • Node.js

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. asset_get the source, then inspect it. Check that its measured shape, runtime and hook area support the brief. If existing hook text must…
  2. Record variants A, B and C with the same source and invariants. Render three exact text cards through scenario-text-overlay, with matching…
  3. Follow scenario-video-assembly: model_schema_get on model_scenario-compose-video, Scenario's single deterministic compositor. Each payload…
  4. Price each exact payload with model_run and dry_run: true. Fit submissions and any planned repairs inside the authorized ceiling. A quote…
  5. Inspect every exported variant at the hook boundaries, throughout the gameplay and on the end card. Check the frames immediately before…
  6. Deliver A, B and C in the requested order via asset_display and asset_download. Include the variant map and measured properties. Preserve…

What it can do on your machine

Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scenario Ad Variants loads about 2.1k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 1,098 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 1,098 words, ~2,126 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-ad-variants/SKILL.md (or your agent's skills folder).
name
scenario-ad-variants
description
Use when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Also for revising one variant or resuming a partially completed batch. Not for a new commercial from a still image, ordinary single-clip grading, or automatic Cartesian combinations.
license
MIT

Scenario Ad Variants

Overview

One supplied source becomes an ordered set of independently specified edits. Preserve what the brief does not change, and keep every output traceable to the same source. A new storyboard from a product still belongs to scenario-video-ads; single-clip utilities to scenario-video-editing. Connection, discovery, submission and recovery follow scenario. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.

Resolve only missing decisions: source, requested variants, exact copy, destination, runtime, audio policy and spend ceiling. Reuse answers already supplied. Distinguish a controlled comparison, where only the agreed variable changes, from creative exploration. Never multiply options into a Cartesian batch unless requested.

Quick reference

Requested changeRouteWhat stays fixed
Hook copy, CTA or end cardscenario-text-overlay, then scenario-video-assemblyUnderlying footage, source audio and all other copy
Cutdown, grade or placementscenario-video-editing, scenario-formatsAgreed source intervals, sequence and focal subject
Background, clothing or object replacementscenario-video with a discovered video-edit memberUnchanged identities, actions, timing and source audio
New shots or conceptscenario-video-adsThis is new creative, not a source-preserving edit

Use deterministic operations when they satisfy the brief. In gameplay capture, replacing a background generatively can also change geometry, UI or mechanic behavior. Do not silently treat such output as faithful gameplay. If preserving those pixels is mandatory and the available route cannot isolate the edit, report the limitation before spending. A generative preservation prompt is a request to verify, not a guarantee.

Source and variant records

Read asset_get for source dimensions, duration and frame rate; inspect the footage, its existing text, cuts and audio. Reference images have explicit roles: identity, product, style or replacement. Assign each variant a stable label and record its source asset, intended delta, invariants, exact copy, output specification and audio policy. Every independent variant starts from the source, never the last generated variant. A requested revision starts from the chosen variant when that is the user's intent.

Keep a compact local record of each variant's state: blocked, planned, submitted, pending, failed or verified; submitted job id; output ids; measured properties; QA outcome. Save the actual submitted payload, not just a prose prompt. A rendered output awaiting review is not verified. Retain completed variants and wait on pending jobs after interruption; a transport failure is reconciled through scenario before any resubmission. Retry only the affected failed variant within the remaining ceiling, keeping its original label. Changing the intended delta creates a revision, not an invisible retry.

For a generative edit, construct the prompt from the requested change, named reference roles, preserved identities/text/actions and the source timing. Use recommend with the need in the user's own words, then model_schema_get to establish supported video inputs, references, durations and audio controls. Never import another provider's duration or prompt-length limits. If the requested precision or media is unsupported, offer the nearest feasible route without promising equivalence.

Worked example: three hook variants from gameplay

The brief supplies a 15-second gameplay clip with audio and requests exactly three 9:16 exports. The hook copy occupies seconds 0 to 2: "Hold the line", "One hit left", and "Can you survive?". The gameplay, audio, runtime and final end card must not change. The source already has a clear hook area.

  1. asset_get the source, then inspect it. Check that its measured shape, runtime and hook area support the brief. If existing hook text must be removed from flattened footage, ask for a clean source or agree a covering panel. Unattended, use a panel only if already authorized and it preserves all required visible content; otherwise mark affected variants blocked on a clean source and continue any independent feasible variants. Do not spend on blocked variants or generate new gameplay to erase text.
  2. Record variants A, B and C with the same source and invariants. Render three exact text cards through scenario-text-overlay, with matching geometry and styling so copy is the only changed variable. Upload the rendered cards through scenario.
  3. Follow scenario-video-assembly: model_schema_get on model_scenario-compose-video, Scenario's single deterministic compositor. Each payload uses the same source video layer and its audio, plus its own card as an image layer at the agreed time. Set canvasMode: "custom" with numeric canvasWidth/canvasHeight, and durationMode: "custom" with duration: 15. Give the source layer string width/height matching the canvas and fit: "contain" to preserve the whole picture without stretching; different source ratios leave bars, and cropping requires authorization. Set the card's string width/height, explicit placement and fit: "contain". Set fps from the measured source rate within the schema's whole-number range; disclose any required rounding. This compositor uses seconds in 0.1 increments; do not promise frame-exact timing beyond that contract.
  4. Price each exact payload with model_run and dry_run: true. Fit submissions and any planned repairs inside the authorized ceiling. A quote is not payload or visual validation. Submit with wait: false, save each job id and use jobs_wait; pending jobs keep their ids.
  5. Inspect every exported variant at the hook boundaries, throughout the gameplay and on the end card. Check the frames immediately before, at and after the requested endpoint: a timeline field does not establish whether the rendered endpoint is inclusive. Compare measured runtime and shape with the source. Check that audio stays synchronized and that the tail is intact. A succeeded job with a missing overlay fails. Report an endpoint mismatch instead of silently shortening the hook to hide it.
  6. Deliver A, B and C in the requested order via asset_display and asset_download. Include the variant map and measured properties. Preserve the payloads and source references for revisions; these are a reconstruction recipe, not a native editable-editor project.
Show full SKILL.md (150 more words)Show less

Verification and common mistakes

For generative edits, inspect a contact-sheet sweep plus frames around important changes, not just the first and last frames. Check identities, original and requested text, objects outside the requested edit, action continuity and audio. When generated audio differs, use the supported assembly route to restore the source track only if the picture still aligns; attaching original audio to retimed action does not fix synchronization. Silent sources remain silent unless the brief asks for sound.

  • Rebuilding every variant after one failed job discards successful work and repeats spend.
  • Changing music, grade and hook together invalidates a copy-only comparison.
  • Requested dimensions and duration are not measured output properties.
  • A new visual treatment is not evidence of a better-performing ad; performance needs a separate campaign experiment.
  • Source reconstruction is not byte identity after re-encoding. Check preserved content and measured synchronization; promise lossless delivery only when the route supports it.

© scenario-labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/scenario-ad-variants of scenario-labs/skills.

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Ad Variants next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scenario Ad Variants compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scenario Ad Variants this skillscenario-labs/skills946—~2.1kAutomated safety check: PassMIT
Procedural LofiIvanWng97/pixtuoid491—~3.5kAutomated safety check: PassMIT
Guizang Social Cardsop7418/guizang-social-card-skill7.4k1 repos~7.8kAutomated safety check: PassAGPL-3.0
Weekly Changelog Videoheygen-com/hyperframes60k—~3.3kAutomated safety check: PassApache-2.0
Anthropic Brand Stylinganthropics/skills180k30 repos~559Automated safety check: PassApache-2.0
MoneyPrinterTurbo Video Generatorharry0703/MoneyPrinterTurbo130k—~2.1kAutomated safety check: WarnMIT

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Questions about Scenario Ad Variants

What does Scenario Ad Variants do?

A skill your agent uses when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants. Scenario Ad Variants is an agent skill from scenario-labs/skills. Use when making multiple independent ad or campaign edits from existing footage with Scenario: hook, CTA, copy, end-card, placement, or targeted visual variants.

When should I use Scenario Ad Variants?

Scenario Ad Variants fits situations like: making multiple independent ad; campaign edits from existing footage with Scenario: hook; targeted visual variants.

How do I install Scenario Ad Variants in Claude Code?

Run `npx skills add scenario-labs/skills --skill scenario-ad-variants -a claude-code`. Or copy the skill folder (skills/scenario-ad-variants in scenario-labs/skills) into .claude/skills/scenario-ad-variants in your project. Claude Code loads it when a task matches its description.

How do I install Scenario Ad Variants in Codex?

Run `npx skills add scenario-labs/skills --skill scenario-ad-variants -a codex`. Or copy the skill folder (skills/scenario-ad-variants in scenario-labs/skills) into .agents/skills/scenario-ad-variants in your project. Codex loads it when a task matches its description.

Can I use Scenario Ad Variants in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scenario-labs/skills --skill scenario-ad-variants -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-ad-variants, .gemini/skills/scenario-ad-variants, .github/skills/scenario-ad-variants and .opencode/skills/scenario-ad-variants in your project.

What does Scenario Ad Variants need to run?

Going by SKILL.md and its folder, Scenario Ad Variants needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Scenario Ad Variants access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Scenario Ad Variants safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scenario Ad Variants use?

Scenario Ad Variants is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scenario Ad Variants use?

About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scenario Ad Variants?

Skills that share tags, products or a category with Scenario Ad Variants: Procedural Lofi (IvanWng97/pixtuoid, 491 stars), Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars), Weekly Changelog Video (heygen-com/hyperframes, 60k stars) and Anthropic Brand Styling (anthropics/skills, 180k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Ad Variants?

scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.

Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.