Web Visuals
glifxyz/glif-mcp-server
Make images, textures, illustrations and background video for a website or app you are building, with Glif, and wire them into the code.
A skill your agent uses when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place…
$ npx skills add scenario-labs/skills --skill scenario-ideogram -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install scenario-labs/skills scenario-ideogram --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-ideogram .claude/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .claude/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogramType 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-ideogram -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install scenario-labs/skills scenario-ideogram --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-ideogram .agents/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .agents/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogram -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install scenario-labs/skills scenario-ideogram --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-ideogram .cursor/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .cursor/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogram--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-ideogram -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install scenario-labs/skills scenario-ideogram --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-ideogram .gemini/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .gemini/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogramInstalls 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-ideogram -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-ideogram .github/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .github/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogram -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-ideogram --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-ideogram .opencode/skills/scenario-ideogram && 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-ideogram" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-ideogram into .opencode/skills/scenario-ideogram/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-ideogram", 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-ideogramA skill your agent uses when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place…
Scenario Ideogram is an agent skill from scenario-labs/skills. Use when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place while keeping its exact size, transparent PNG generation, background removal that keeps hair and glass edges, editable text layers for localization, or one consistent character from a reference. Keywords: Ideogram 4.5, Precise Edit, V4, V3, typography, aspect ratio, layerize, character reference, inpainting.
Its SKILL.md is about 2.7k 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, covering Image editing, Internationalization and Logo and visual identity. It works with Model Context Protocol. 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.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 91caa01. 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:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Scenario Ideogram loads about 2.7k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 1,385 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 91caa01, republished under its MIT licence (© scenario-labs). 1,385 words, ~2,664 tokens.
.claude/skills/scenario-ideogram/SKILL.md (or your agent's skills folder).Ideogram's image family on Scenario is a set of single-purpose members, not one model with modes: 4.5 for generation where in-image text must read and for reference-guided edits, 4.5 Precise Edit for changing one thing and leaving the rest alone, V3 Generate Transparent for native alpha output, V3 Layerize Text for turning a flat graphic into editable text layers, Character for one identity held across scenes, and Remove Background for cutouts. V4 still answers searches but was tagged deprecated in favor of 4.5 at authoring time. The members agree on almost nothing mechanically: the same concept changes name, casing, and allowed values between them, so discover each with search and treat its model_schema_get as the contract.
Connection and the core loop: see the scenario skill in this repo; model-agnostic image work (sizing families, reference cardinality, masks): the scenario-image skill; running a bake-off against another family: scenario-model-comparison. 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.
Pick the member by the job (names from the live schemas, caps at authoring time):
| Member | Job | Inputs that matter |
|---|---|---|
| 4.5 | Text-heavy generation, ref edits | prompt, referenceImages (up to 5, the first is the source), mask, aspectRatio (auto, source, 25 ratios from 3:1 to 1:3), resolution (1K, 2K), quality, magicPrompt, numOutputs (up to 8) |
| 4.5 Precise Edit | Change one thing, keep the rest | image (output keeps its size), mask, referenceImages (up to 4 guides), quality (default medium), numOutputs (up to 8) |
| V3 Generate Transparent | Native alpha output | prompt, negativePrompt, aspectRatio (15 ratios), renderingSpeed (adds FLASH), expandPrompt, numOutputs (up to 8), seed |
| V3 Layerize Text | Flat graphic to layers | image, optional prompt, fontName* or fontFile* per tier (H1, H2, Body, Small), seed |
| Character | Same character, new scenes | prompt, characterReferenceImage, styleType (Auto, Fiction, Realistic), aspectRatio or resolution, image plus mask, renderingSpeed (Default, Turbo, Quality), seed |
| Remove Background | Cutout to transparent PNG | image (10MB cap) |
Nothing transfers between members. Masks flip between them: on 4.5 and Precise Edit white marks the region to edit, on Character black repaints and white stays. Only V3 Transparent takes a negativePrompt. renderingSpeed is uppercase on V3 Transparent and Title case on Character, whose middle tier is Default.
quality is the price dial on both 4.5 members (very_low, low, medium, high; very_low needs an input image, which Precise Edit's image satisfies and 4.5 takes as a referenceImages entry). At authoring time dry_run quoted 7.75, 13.75, and 41.75 CU for low, medium, and high, Precise Edit's very_low 3.75, and the same figure at 1K and 2K and for a 0.4 MP, 4.3 MP, or 8.3 MP source; billed jobs came in 1.75 CU under each estimate. 4.5 defaults to high, its top and most expensive tier; Precise Edit defaults to medium, and its high picks the best of several candidates at three times the price. Tier names do not line up across families: Ideogram's high is its ceiling, while GPT Image 2.5's high is its third tier of five and priced near Ideogram's medium. Compare families at a matched price, never a matched tier name, and dry_run the exact payload.
2K output observed at authoring time: 2048 by 2048 (1:1), 2560 by 1440 (16:9), 2880 by 1440 (2:1), 2944 by 1152 (23:9), 3072 by 1024 (3:1), so the long edge tops out near 3072 and there is no 4K. 1K is about 1 MP (16:9 returned 1280 by 720) and exists only for 1:1, 4:5, 3:4, 2:3, 5:8, 9:16, 1:2 and their landscape counterparts; 3:1 at 1K passes dry_run, then fails at run time with a hint naming the fix. A ratio outside the list (4:1) is a 400 listing the allowed values. A mask requires aspectRatio: "auto".
For an edit, aspectRatio: "source" on 4.5 and every Precise Edit run return the source's exact pixel size, even one outside the ratio list: a 1326 by 313 (4.24:1) turnaround sheet came back 1326 by 313 from both, while auto rebuilt it as a full 3072 by 1024 scene. Use this when the edited file must drop back into a layout, a sprite sheet, or a page template unchanged. A localized change such as a headline swap needs no mask on Precise Edit: maskless at the medium default left the rest of the scene untouched. The GPT Image family pads such a source with white bands instead (see scenario-gpt-image).
In a single-sample bake-off at authoring time against GPT Image 2.5 on the same sources, the 4.5 members disturbed two to four times fewer pixels outside the edited region on a sign-text swap and an add-and-remove-objects edit, and read closer to a requested painterly medium (a watercolor restyle, a gouache landscape; hands-on use found the same for pencil sketches). GPT Image 2.5 led on photoreal product shots, on following a character brief, and on material and color changes: asked for burnished gold armor, both 4.5 members returned an olive brass, and Precise Edit also recolored the sword the prompt said to keep. Route by the job, and say "keep everything else exactly the same" plus the list of what must survive in every edit prompt.
The generators rewrite the prompt before generating by default, which helps a short exploratory prompt and hurts the family's specialty: the rewrite can paraphrase the exact copy that must render. When the image carries wording, disable it (magicPrompt: "off" on 4.5, expandPrompt: false on V3 Transparent), quote each piece of copy, and give it a place and a style ('the headline reads "GRAND OPENING" in bold condensed capitals across the top'). magicPrompt applies to text-to-image only: 4.5 turns every edit into structured instructions regardless.
Native: V3 Generate Transparent writes the alpha channel directly, so icons, stickers, and UI elements arrive compositing-ready. Cutout: generate on 4.5, then run Remove Background on the result; it reconstructs edge pixels with partial transparency rather than segmenting, so hair, fur, and glass survive. Go native when the asset is designed as an isolated element; go cutout when typography or overall quality leads. 4.5 has no background field, so prompting "transparent background" there yields an opaque image.
search with target="models", query="ideogram", public=true. Members return as separate hits; match by name, e.g. model_ideogram-v4-5 for typography (a live hit at authoring time: re-discover each session).model_schema_get with that id: field names, allowed values, and defaults before anything else.model_run with that model_id, dry_run=true, and parameters={"prompt": "Retro travel poster, warm dusk palette. The headline reads \"KYOTO IN BLOOM\" in bold serif across the top; caption \"April 2027\" bottom right.", "aspectRatio": "9:16", "resolution": "2K", "quality": "high", "magicPrompt": "off", "numOutputs": 2} for the cost estimate.model_run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.asset_display the outputs and pick one.model_ideogram-v3-layerize-text at authoring time), read its schema, and model_run with parameters={"image": "<poster asset id>"}: a generated asset's id feeds a file input directly, no re-upload. The output is a text-erased base plus text blocks with role, position, and content.jobs_wait, then asset_display and asset_download.magicPrompt and resolution are 4.5's; V3 Transparent wants aspectRatio and expandPrompt; Precise Edit takes image, not referenceImages, for the source.aspectRatio: "auto" when the canvas must not change: use source, or Precise Edit.image but no mask: they go together, characterReferenceImage stays required, and sizing fields are ignored while inpainting.fontNameH1 and fontFileH1 together on Layerize: a tier's font comes from a font name or a font file, never both. upload_asset has no font kind, so with only a local font file use the font name route and flag the gap.© 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-ideogram of scenario-labs/skills.
Open the folder on GitHubat commit 91caa01
Scenario Ideogram 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 Ideogram this skillscenario-labs/skills | 931 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Web Visualsglifxyz/glif-mcp-server | 212 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Olore Recraft Latestolorehq/olore | 104 | — | ~773 | Automated safety check: Pass | MIT | |
| Image Prompt ReverseLunarXuan/image-prompt-reverse | 479 | — | ~678 | Automated safety check: Pass | GPL-3.0 | |
| App Icons And Logosglifxyz/glif-mcp-server | 212 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Nous Brandingmagnus919/agent-skills | 116 | — | ~4k | Automated safety check: Pass | MIT |
glifxyz/glif-mcp-server
Make images, textures, illustrations and background video for a website or app you are building, with Glif, and wire them into the code.
olorehq/olore
Local recraft documentation reference (latest). An agent skill from olorehq/olore.
LunarXuan/image-prompt-reverse
Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts.
glifxyz/glif-mcp-server
Design a logo, app icon, favicon set, icon set or brand kit with Glif for an app or site you are building, then export every size and wire it into the code.
magnus919/agent-skills
Generate images and content consistent with the Nous Research brand identity.
thatrebeccarae/claude-marketing
Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json.
scenario-labs/skills
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Works with
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A skill your agent uses when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place…. Scenario Ideogram is an agent skill from scenario-labs/skills. Use when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place while keeping its exact size, transparent PNG generation, background removal that keeps hair and glass edges, editable text layers for localization, or one consistent character from a reference.
Scenario Ideogram fits situations like: editing images with Ideogram models on Scenario via MCP: posters; signage with exact in-image text; editing an image in place while keeping its exact size; transparent PNG generation.
Run `npx skills add scenario-labs/skills --skill scenario-ideogram -a claude-code`. Or copy the skill folder (skills/scenario-ideogram in scenario-labs/skills) into .claude/skills/scenario-ideogram in your project. Claude Code loads it when a task matches its description.
Run `npx skills add scenario-labs/skills --skill scenario-ideogram -a codex`. Or copy the skill folder (skills/scenario-ideogram in scenario-labs/skills) into .agents/skills/scenario-ideogram 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-ideogram -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-ideogram, .gemini/skills/scenario-ideogram, .github/skills/scenario-ideogram and .opencode/skills/scenario-ideogram in your project.
Going by SKILL.md and its folder, Scenario Ideogram needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
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.
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 Ideogram is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k 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 Ideogram: Web Visuals (glifxyz/glif-mcp-server, 212 stars), Olore Recraft Latest (olorehq/olore, 104 stars), Image Prompt Reverse (LunarXuan/image-prompt-reverse, 479 stars) and App Icons And Logos (glifxyz/glif-mcp-server, 212 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 931 GitHub stars. The repository holds 143 skills in this directory. The repository was last updated on October 8, 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.