image-poster

nexu-io/open-design · Agent Skill

Generates images for posters, key art, and illustrations, utilizing various selectable models.

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Overview

Publishernexu-ioOrganization
Repositorynexu-io/open-design ↗
Skill folderimage-poster
Stars95,886
Forks11,122
Bundled files2
LicenseApache-2.0
Last updatedSeptember 13, 2026
LinksSkill source ↗ · Repository ↗

Mozgi check

What we found in the skill files. Details come with a subscription.

Security
low risk · no obvious risks found — the full report shows the details
Compatibility
instructions only — works with most agents
Similar skills
37 similar skills found
Also with subscription

Installation

A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.

Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.

Install the “image-poster” skill from mozgi.io (https://mozgi.io/skills/image-poster/) for me.

1. Download the archive: https://mozgi.io/skills/image-poster/download
   If it fails, take the skill folder from the source: https://github.com/nexu-io/open-design/tree/main/design-templates/image-poster
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “image-poster” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/image-poster/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

Review the source files

2 files Download Zip

Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.

SKILL.md contents

Original author text · read-only

Image Poster Skill

Produce one finished image asset per turn unless the user asks for

variations. Image generation rewards a tight, structured prompt — your

job is to assemble that prompt from the user's brief, then dispatch.

Resource map

image-poster/
├── SKILL.md         ← you're reading this
└── example.html     ← what the resulting card looks like in Examples

Workflow

Step 0 — Read the project metadata

The active project carries imageModel, imageAspect, and (optional)

imageStyle notes. Use them as the upstream model + canvas + style

anchor. When a value is not provided, infer a safe default from the brief and

media contract. Ask only when the choice would materially change the requested

result and no safe default can be inferred.

Step 1 — Compose the prompt

Plan in this exact order before calling any tool:

1. Subject + composition — what is in the frame, where, at what

scale; eye-line and crop.

2. Lighting + mood — natural / studio / moody; warm / cool; key

plus rim plus fill; time of day if outdoor.

3. Palette + textures — hex anchors when the user gave a brand

palette; otherwise a 3-word mood tag (e.g. "muted ochre + ink").

4. Camera / lens — only if the user wants photographic realism

("85mm portrait, shallow DOF") or a specific film stock.

5. What to avoid — common AI-slop patterns ("no extra fingers, no

warped text, no logo placeholders").

Step 2 — Dispatch via the media contract

Use the unified dispatcher — do not call upstream provider APIs by

hand. Run from your shell tool:

"$OD_NODE_BIN" "$OD_BIN" media generate \
  --project "$OD_PROJECT_ID" \
  --surface image \
  --model "<imageModel from metadata>" \
  --aspect "<imageAspect from metadata>" \
  --output "<short-descriptive-name>.png" \
  --prompt "<the full assembled prompt from Step 1>"

The command prints one line of JSON: {"file": {"name": "...", ...}}.

The daemon writes the bytes into the project folder; the FileViewer

picks it up automatically.

Step 3 — Hand off

Reply with a one-paragraph summary of the prompt you used and the

filename returned by the dispatcher (e.g. *I generated hero-poster.png

with gpt-image-2 at 1:1.*). Do not emit an <artifact> tag.

Hard rules

  • One image per turn unless asked for variations.
  • Honor imageAspect exactly — the upstream cost is the same; matching

the aspect avoids a re-render.

  • No filler typography in the image itself unless the user asked for

in-frame text. Real copy beats lorem.

  • Save every render — never describe an image without producing the

file. The user expects something to open in the file viewer.

Frequently asked questions

What does the image-poster skill do?

Generates images for posters, key art, and illustrations, utilizing various selectable models.

How do I install image-poster?

Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.

Which AI models work with image-poster?

Skills are plain Markdown instructions (the Agent Skills format), so image-poster works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.

Is image-poster free?

The skill is published openly by nexu-io under the Apache-2.0 license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.

Is it safe to install skills?

A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.

How is a skill different from an MCP server or a plugin?

An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.

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