Source profileQuality 73/100Review permissions

nexu-io/open-design/design-templates/image-poster/SKILL.md

image-poster

Single-image generation skill for posters, key art, and editorial illustrations. Defaults to gpt-image-2 but is provider-agnostic — the same workflow drives Flux, Imagen, or Midjourney via the active upstream tooling. Output is one or more PNG/JPEG files saved to the project folder.

Source repository stars
82,073
Declared platforms
0
Static risk flags
2
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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.

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/nexu-io/open-design --skill "design-templates/image-poster"
    Safe inspection promptEditorial

    Inspect the Agent Skill "image-poster" from https://github.com/nexu-io/open-design/blob/89d6d4ef21baf80f871595abdf6f7de6e941dd44/design-templates/image-poster/SKILL.md at commit 89d6d4ef21baf80f871595abdf6f7de6e941dd44. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Workflow

      The active project carries imageModel, imageAspect, and (optional) imageStyle notes. Use them as the upstream model + canvas + style anchor; only ask the user to fill them in if they're marked (unknown — ask).

      Subject + composition — what is in the frame, where, at whatLighting + mood — natural / studio / moody; warm / cool; keyPalette + textures — hex anchors when the user gave a brand
    2. 02

      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; only ask the user to fill them in if they're marked (unknown — ask).

      The active project carries imageModel, imageAspect, and (optional) imageStyle notes. Use them as the upstream model + canvas + style anchor; only ask the user to fill them in if they're marked (unknown — ask).
    3. 03

      Step 1 — Compose the prompt

      Plan in this exact order before calling any tool:

      Subject + composition — what is in the frame, where, at whatLighting + mood — natural / studio / moody; warm / cool; keyPalette + textures — hex anchors when the user gave a brand
    4. 04

      Step 2 — Dispatch via the media contract

      Use the unified dispatcher — do not call upstream provider APIs by hand. Run from your shell tool:

      Use the unified dispatcher — do not call upstream provider APIs by hand. Run from your shell tool:The command prints one line of JSON: {"file": {"name": "...", ...}}. The daemon writes the bytes into the project folder; the FileViewer picks it up automatically.

    Permission review

    Static risk signals and limitations

    Runs scripts

    medium · line 42

    The documentation asks the agent to run terminal commands or scripts.

    hand. Run from your shell tool:

    Reads files

    low · line 72

    The documentation asks the agent to read local files, directories, or repositories.

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

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score73/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars82,073SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    nexu-io/open-design
    Skill path
    design-templates/image-poster/SKILL.md
    Commit
    89d6d4ef21baf80f871595abdf6f7de6e941dd44
    License
    Apache-2.0
    Collected
    2026-07-28
    Default branch
    main
    View the original SKILL.md

    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; only ask the user to fill them in if they're marked (unknown — ask).

    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.

    Alternatives

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