Od Brand Guidelines
criptogus/agent-evolve-network
Apply Anthropic's official brand colors and typography to artifacts for consistent visual identity and professional design standards Use when the user asks for brand guidelines work, or mentions od…
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…
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install scenario-labs/skills scenario-brand-kit --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .claude/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kitType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install scenario-labs/skills scenario-brand-kit --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/scenario-brand-kit .agents/skills/scenario-brand-kit && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .agents/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install scenario-labs/skills scenario-brand-kit --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/scenario-brand-kit .cursor/skills/scenario-brand-kit && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .cursor/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/scenario-labs/skills.git --path skills/scenario-brand-kit--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install scenario-labs/skills scenario-brand-kit --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/scenario-brand-kit .gemini/skills/scenario-brand-kit && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .gemini/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install scenario-labs/skills scenario-brand-kitInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/scenario-brand-kit .github/skills/scenario-brand-kit && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .github/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-brand-kit -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install scenario-labs/skills scenario-brand-kit --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/scenario-brand-kit .opencode/skills/scenario-brand-kit && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "scenario-brand-kit" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-brand-kit into .opencode/skills/scenario-brand-kit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-brand-kit", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
scenario-brand-kitA 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. 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.
8 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
curlnpxFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 1,541 words, ~3,372 tokens.
.claude/skills/scenario-brand-kit/SKILL.md (or your agent's skills folder).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.
| Need | Route |
|---|---|
| The spec | Written first, by you with the user, before any generation: contents under The spec sheet |
| Logo, native | recommend 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, traced | An existing raster mark: recommend capability="img2img", the prompt saying trace to editable SVG, do not regenerate |
| Gate | asset_analyze the mark with the spec via text_inputs; a drifted wordmark is re-run, never patched |
| Variants | asset_get the mark, save its url (curl -L) for the stored SVG, recolor locally, upload_asset each variant |
| Applications | recommend with capability="img2img", approved mark as reference, spec hex values in the prompt, one placement per run |
| Icon strip | The 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 board | model_scenario-compose-image (first-party compositor, id fixed): mark, swatches, specimen, applications as positioned layers, labels via scenario-text-overlay |
| File the kit | collection_create before the first run, collection_add_assets each keeper as it lands, asset_update for each one's role and rule |
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.
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.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).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.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.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.scenario-text-overlay in the spec's type, never prompted into the plate. Placement sizes derive per scenario-formats.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.asset_update description, and deliver the spec sheet as the kit's usage page.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
Just SKILL.md in skills/scenario-brand-kit of scenario-labs/skills.
Open the folder on GitHubat commit f6f8ab7
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Scenario Brand Kit this skillscenario-labs/skills | 946 | — | ~3.4k | Automated safety check: Pass | MIT | |
| Od Brand Guidelinescriptogus/agent-evolve-network | 288 | — | ~831 | Automated safety check: Pass | Apache-2.0 | |
| Brand Dnathatrebeccarae/claude-marketing | 161 | — | ~1.8k | Automated safety check: Pass | MIT | |
| 46 Brand Guideline Globalminhnv0807/ai-business-skills | 609 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Brandingkostja94/marketing-skills | 1k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Magic Hour Brand Kithashgraph-online/awesome-codex-plugins | 1.3k | — | ~1.1k | Automated safety check: Pass | MIT |
criptogus/agent-evolve-network
Apply Anthropic's official brand colors and typography to artifacts for consistent visual identity and professional design standards Use when the user asks for brand guidelines work, or mentions od…
thatrebeccarae/claude-marketing
Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json.
minhnv0807/ai-business-skills
A skill your agent uses when brand VISUAL rules have to be created or updated — brand personality, color system, typography, logo usage, imagery and visual tone, component rules, accessibility…
kostja94/marketing-skills
When the user wants to define, audit, or apply brand strategy—purpose, values, positioning, storytelling, voice, narrative (not only visuals).
hashgraph-online/awesome-codex-plugins
Create, extend or apply a reusable brand kit with Magic Hour imagery, exact logos and colors, editable layouts and a practical brand guide.
Ohh-889/skyroc
Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations…
scenario-labs/skills
A skill your agent uses when drawing or animating with Grease Pencil in Blender 5.x from Python: 2D or 2.5D illustration, frame-by-frame animation, a cutout or part-based 2D character, strokes with…
scenario-labs/skills
A skill your agent uses when grooming hair or fur in Blender with hair curves, such as a character hairstyle, animal fur, procedural fur in geometry nodes, or hair cards and mesh hair for games.
scenario-labs/skills
A skill your agent uses when lighting, rendering or compositing in Blender: light a character, product or hero shot, interior at dusk or night, three-point or motivated lighting, sun and sky, HDRI…
scenario-labs/skills
A skill your agent uses when creating a ChatGPT pet or Codex pet with Scenario: hatching an animated companion from a text idea, a character, mascot or brand cue, or reference photos and art; making…
scenario-labs/skills
A skill your agent uses when animating characters or scenes in Godot 4.7: AnimationPlayer clips and RESET, AnimationTree state machines and blend spaces built in code, Mixamo or glTF import, loop…
scenario-labs/skills
A skill your agent uses when adding or fixing sound in Godot 4.7: audio buses and effects, volume sliders, 'too many sounds', combat audio with hundreds of enemies, sounds clipping or distorting, 3D…
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.