Image Poster Skill
SkillFiles & storageimage-poster is a skill that lets an AI agent create a single poster, cover-art, or illustration image from a written brief. It composes a detailed image prompt covering subject, lighting, palette, and camera details, then runs one dispatcher command to generate the picture. The skill defaults to gpt-image-2 but is provider-agnostic, so the same workflow can drive Flux, Imagen, or Midjourney through the active upstream tooling. Results are saved as PNG or JPEG files in the project folder.
Use Image Poster Skill in Claude, ChatGPT or Ahel Desktop
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Then ask your AI: use the Image Poster Skill skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
No other account needed.
Have a project folder where generated images should be saved.
What your AI can do with it
- Compose a detailed image prompt from a written brief
- Cover subject, lighting, palette, and camera details
- Run a single dispatcher command to generate the image
- Default to gpt-image-2 for generation
- Drive Flux, Imagen, or Midjourney via upstream tooling
- Save one or more PNG or JPEG files to the project folder
Getting started
- Have a project folder where generated images should be saved.
- Make sure the active upstream tooling for your chosen image model is available.
- Write a brief describing the poster, cover art, or illustration you want.
- Let the skill compose the detailed prompt and run the dispatcher command.
- Find the resulting PNG or JPEG files in the project folder.
What this skill tells your AI
The instructions your AI receives, as published by nexu-io/open-design in design-templates/image-poster/SKILL.md and read by ahel’s review.
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:
- Subject + composition — what is in the frame, where, at what scale; eye-line and crop.
- Lighting + mood — natural / studio / moody; warm / cool; key plus rim plus fill; time of day if outdoor.
- Palette + textures — hex anchors when the user gave a brand palette; otherwise a 3-word mood tag (e.g. "muted ochre + ink").
- Camera / lens — only if the user wants photographic realism ("85mm portrait, shallow DOF") or a specific film stock.
- 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
imageAspectexactly — 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.
Signals
- GitHub stars
- 99k
- Forks
- 11k
- Last commit
- Oct 2026
Questions
- What kind of output does image-poster produce?
- It produces one or more PNG or JPEG image files saved to the project folder.
- Which image models can it use?
- It defaults to gpt-image-2 but is provider-agnostic, so it can drive Flux, Imagen, or Midjourney through the active upstream tooling.
- What does the skill do before generating the image?
- It composes a detailed image prompt covering subject, lighting, palette, and camera details, then runs a single dispatcher command.
Advanced
- Item type
- skill
- Key
image-poster-nexu-io- Source
- github.com/nexu-io/open-design
github.com/nexu-io/open-design