Agent skill

Scenario Brand Kit

by scenario-labs in scenario-labs/skills

A skill your agent uses when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed…

MITAuto-check passedMarketing & SEO

Install Scenario Brand Kit

skills CLI
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a claude-code

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

GitHub CLI
$ gh skill install scenario-labs/skills scenario-brand-kit --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-brand-kit .claude/skills/scenario-brand-kit && 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-brand-kit
GitHub stars
946
Token cost
~3.4k tokens
SKILL.md length
1,541 words
Files
1
Skills in repo
146
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed…

  • Works in 8 steps: Spec first. Name the category, the… → Mark: recommend with… → Gate the pick with asset_analyze (write… → …
  • Building a visual identity
  • SKILL.md covers Overview, Quick reference, The spec sheet and Worked example: an identity…, plus 1 more section
  • Calls curl and npx

What it does

Scenario Brand Kit is an agent skill from scenario-labs/skills. Use when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed, favicon), and brand applications like social templates, avatars, banners, or merchandise mockups. Also for a rebrand or refreshing an existing mark. Keywords: brandkit, brand kit, visual identity, logo, monogram, wordmark, SVG, vectorize, color palette, typography, brand guidelines, brand board, launch kit.

Its SKILL.md is about 3.4k 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 Marketing & SEO, covering Brand strategy and identity and Logo and visual identity. 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

  • Building a visual identity
  • Brand kit with Scenario: a logo
  • Icon as editable SVG
  • A color palette and typography spec

Example prompts

  • “/scenario-brand-kit”

Requirements

  • Node.js

Workflow steps

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

  1. Spec first. Name the category, the audience, the promise and the core metaphor before anything is written down, since step 2's mark comes…
  2. Mark: recommend with capability="txt2img" and a prompt demanding a real editable SVG and not a raster; model_schema_get the pick. Prompt…
  3. Gate the pick with asset_analyze (write lane, contract in scenario-asset-analysis), the spec via text_inputs: name read letter by letter…
  4. Variants: asset_get the winning mark and save its url with curl -L, which serves the stored SVG verbatim (asset_download converts to…
  5. Applications: recommend with capability="img2img", skipping a pick whose when_general_better or caveats name the placement at hand; wire…
  6. Exact text (tagline, handle, URL) is composited by scenario-text-overlay in the spec's type, never prompted into the plate. Placement…
  7. Board: the kit is judged as one picture. model_scenario-compose-image takes the mark, palette swatches, a type specimen, the voice line…
  8. The collection, filled as the run went, is the kit: the SVG master, every variant, every application, the board. Write each asset's role…

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:

    • curl
    • npx

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

  • Network

    No URLs in SKILL.md. Its commands use curl and 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 Brand Kit loads about 3.4k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 1,541 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

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). 1,541 words, ~3,372 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-brand-kit/SKILL.md (or your agent's skills folder).
name
scenario-brand-kit
description
Use when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed, favicon), and brand applications like social templates, avatars, banners, or merchandise mockups. Also for a rebrand or refreshing an existing mark. Keywords: brandkit, brand kit, visual identity, logo, monogram, wordmark, SVG, vectorize, color palette, typography, brand guidelines, brand board, launch kit.
license
MIT

Scenario Brand Kit

Overview

An identity is decided, then rendered. Palette and typography are choices written into a spec before any run; the logo is generated once as a real vector and reused everywhere; every application references the approved mark instead of re-imagining it. Connection and the core loop: see the scenario skill. Finding the direction when nothing is decided: scenario-inspiration. Image runs and reference wiring: scenario-image. Exact taglines and CTAs on applications: scenario-text-overlay. Per-placement sizes: scenario-formats. Gating contract: scenario-asset-analysis. 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.

Quick reference

NeedRoute
The specWritten first, by you with the user, before any generation: contents under The spec sheet
Logo, nativerecommend capability="txt2img", the prompt demanding a real editable SVG and not a raster: that clause, not the capability, is what surfaces the vector generator; skip a style member ranked first (it refuses a run without style inputs, see Icon strip) for the plain SVG sibling, found by search on the same name
Logo, tracedAn existing raster mark: recommend capability="img2img", the prompt saying trace to editable SVG, do not regenerate
Gateasset_analyze the mark with the spec via text_inputs; a drifted wordmark is re-run, never patched
Variantsasset_get the mark, save its url (curl -L) for the stored SVG, recolor locally, upload_asset each variant
Applicationsrecommend with capability="img2img", approved mark as reference, spec hex values in the prompt, one placement per run
Icon stripThe vector generator's style members (search, filters={"tags": ["style-consistency", "svg"]}; its plain SVG members expose no image field): raster renders of the mark (asset_download with format png returns a raster of the stored SVG) as styleReferenceImages on the first icon, then that job's style_id (job_get, verbose=true, output metadata) as styleId on the rest, never both
The boardmodel_scenario-compose-image (first-party compositor, id fixed): mark, swatches, specimen, applications as positioned layers, labels via scenario-text-overlay
File the kitcollection_create before the first run, collection_add_assets each keeper as it lands, asset_update for each one's role and rule

The spec sheet

One short document anchors every run and every gate: four to six hex values, each with a role (primary, ink, paper, accent), the accent recurring on every asset because a second accent reads as none; two type families with weights and their jobs (display, body); one voice line, short and specific rather than a slogan; the logo's clear space and minimum size; three "never" rules (never stretch, never recolor outside the palette, never set the wordmark in another face). Prompts name hex values from it verbatim, and every gate hands its full text to asset_analyze through text_inputs (a paraphrase drops exact spelling and hex roles). Type comes from families the destination can load (widely available or licensed): a generated "font" is a picture of one, so real text is set by scenario-text-overlay in the spec's family. The wordmark is the exception: it is drawn once into the mark, gated letter by letter, and reused as artwork from then on.

Worked example: an identity for a new game studio

  1. Spec first. Name the category, the audience, the promise and the core metaphor before anything is written down, since step 2's mark comes out of that metaphor. The brief names a mood; scenario-inspiration turns it into a chosen direction when it names nothing. Write palette, type, and rules down before any generation and confirm with the user (unattended: take the brief's constraints, decide the rest, mark it provisional). Create this run's collection before the first generation (collection_create, catalog write lane, name only), then collection_add_assets each keeper as it lands; its returned itemCount is the receipt.
  2. Mark: recommend with capability="txt2img" and a prompt demanding a real editable SVG and not a raster; model_schema_get the pick. Prompt one idea about what the studio makes, reduced until it still reads in one color at favicon size: flat closed geometry, few colors, the spec's hex values, the studio name for the wordmark. Say what to avoid or the model reaches for its defaults (gradient mesh, sparkles, an unmotivated bolt, a globe). A pick that rejects a schema-conformant call is spent: take the next option rather than debugging it, since a schema can mark a field optional that the model requires. Three candidates, each on a different construction method and combining no more than two of them, so the set spans an axis rather than reseeding one idea: monogram fused with the metaphor, the product's verb as a symbol, two ideas reduced to one, negative space carrying a second reading, geometry on a stated grid. Pass priority="cost" on this round, since two of the three are discarded and recommend otherwise defaults to the quality pick. One model_run per candidate, jobs_wait, asset_display, and let the user pick (unattended: gate all, keep the best pass).
  3. Gate the pick with asset_analyze (write lane, contract in scenario-asset-analysis), the spec via text_inputs: name read letter by letter, geometry closed and centered, no resemblance to an existing mark. It gates the render, not the file (scenario-asset-analysis), so the palette check is a local parse of the SVG's fills. Fail means re-run with the prompt tightened (jobs_wait the new job before re-gating), never an edit of the drifted output.
  4. Variants: asset_get the winning mark and save its url with curl -L, which serves the stored SVG verbatim (asset_download converts to raster, format defaulting to png). Recolor fills to make mono, reversed, and paper-background variants; upload_asset each (kind image). One mark, colorways as data.
  5. Applications: recommend with capability="img2img", skipping a pick whose when_general_better or caveats name the placement at hand; wire the approved mark as reference exactly as the schema says (an array only under array: true; a pick whose schema has no image field cannot hold the mark, so take the next option). One model_run per placement (avatar, banner, printed card or badge), each prompt subordinating the scene to the mark and barring lettering or fake UI from the frame (a plate shows the mark in place, not the product working): "the exact logo from the reference, unaltered, centered on...". jobs_wait the runs, then gate each against the spec; text the gate cannot resolve at output size is unverified, not passed (upscale and re-gate, or flag it), and a scene that mangled the mark goes back through the same img2img call, the prompt naming the defect with the approved mark as ground truth.
  6. Exact text (tagline, handle, URL) is composited by scenario-text-overlay in the spec's type, never prompted into the plate. Placement sizes derive per scenario-formats.
  7. Board: the kit is judged as one picture. model_scenario-compose-image takes the mark, palette swatches, a type specimen, the voice line set large, an image-direction plate (one more run), an icon and badge strip and two applications as layers placed by x, y, anchor and zIndex on a canvasMode: "custom" canvas, plus a construction panel drawn locally from the master SVG, never generated (a generated diagram shows geometry the mark does not have), panel labels rendered by scenario-text-overlay (layer fields and traps: scenario-video-assembly). Give every layer an explicit width and height, the mark's larger than any other, each with fit: "contain": empty is documented as native size and is not reliable, and setting both dimensions activates the default fill, which stretches and breaks the spec's own never-stretch rule. Size the canvas for the smallest caption rather than for a screen (it takes up to 7680x4320, and a 1920x1080 board left palette captions near ten pixels tall), and render each layer from the master SVG at the pixel size that layer occupies instead of reusing one raster everywhere: the vector master exists so that no layer is ever upscaled. upload_asset each render before composing, since a layer source takes an asset, not a local file.
  8. The collection, filled as the run went, is the kit: the SVG master, every variant, every application, the board. Write each asset's role and rule into its asset_update description, and deliver the spec sheet as the kit's usage page.
Show full SKILL.md (194 more words)Show less

Common mistakes

  • Generating applications before a spec exists: without written hex values and rules there is nothing to gate against, and the kit drifts apart asset by asset.
  • Re-imagining the logo per application instead of referencing it: ten cousins, no identity. The mark is generated once, then reused.
  • Upscaling a raster of the logo: the vector already scales; the SVG stays the master.
  • Recoloring by regenerating: fills and strokes in an SVG are text edits; a regeneration changes the geometry too.
  • Passing a wordmark that looks right at thumbnail size: letterform drift hides there; the gate reads it back letter by letter.
  • Treating palette hex values as a vibe: unnamed colors drift warm or cool per run; every prompt names them from the spec.
  • Uploading a variant that is byte-identical to the master: the platform returns the master's own asset id, so two kit entries silently collapse into one and the collection count is wrong. A variant that changes nothing is not a variant; edit a fill, or drop the baked ground path, before uploading.
  • Deriving a variant from a mockup instead of the master: derivative-of-derivative compounds artifacts (scenario-formats has the order of operations).

© 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-brand-kit of scenario-labs/skills.

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Brand Kit 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 Brand Kit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scenario Brand Kit this skillscenario-labs/skills946—~3.4kAutomated safety check: PassMIT
Od Brand Guidelinescriptogus/agent-evolve-network288—~831Automated safety check: PassApache-2.0
Brand Dnathatrebeccarae/claude-marketing161—~1.8kAutomated safety check: PassMIT
46 Brand Guideline Globalminhnv0807/ai-business-skills609—~3.2kAutomated safety check: PassMIT
Brandingkostja94/marketing-skills1k—~2.3kAutomated safety check: PassMIT
Magic Hour Brand Kithashgraph-online/awesome-codex-plugins1.3k—~1.1kAutomated safety check: PassMIT

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Questions about Scenario Brand Kit

What does Scenario Brand Kit do?

A skill your agent uses when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed…. Scenario Brand Kit is an agent skill from scenario-labs/skills. Use when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed, favicon), and brand applications like social templates, avatars, banners, or merchandise mockups.

When should I use Scenario Brand Kit?

Scenario Brand Kit fits situations like: building a visual identity; brand kit with Scenario: a logo; icon as editable SVG; A color palette and typography spec.

How do I install Scenario Brand Kit in Claude Code?

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

How do I install Scenario Brand Kit in Codex?

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

Can I use Scenario Brand Kit 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-brand-kit -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-brand-kit, .gemini/skills/scenario-brand-kit, .github/skills/scenario-brand-kit and .opencode/skills/scenario-brand-kit in your project.

What does Scenario Brand Kit need to run?

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

Does Scenario Brand Kit access the network?

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

Is Scenario Brand Kit 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 Brand Kit use?

Scenario Brand Kit 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 Brand Kit use?

About 3.4k tokens (SKILL.md is roughly 13k 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 Brand Kit?

Skills that share tags, products or a category with Scenario Brand Kit: Od Brand Guidelines (criptogus/agent-evolve-network, 288 stars), Brand Dna (thatrebeccarae/claude-marketing, 161 stars), 46 Brand Guideline Global (minhnv0807/ai-business-skills, 609 stars) and Branding (kostja94/marketing-skills, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Brand Kit?

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.