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).
nexu-io/open-design
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.
npx skills add https://github.com/nexu-io/open-design --skill "design-templates/image-poster"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
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.
npx skills add https://github.com/nexu-io/open-design --skill "design-templates/image-poster"The pinned source supports a structured brief, but not an expanded tutorial. Only detected inputs, outputs, and sections are shown.
375 source words · 7 usable sections
Content workflow
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
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).
Plan in this exact order before calling any tool:
Use the unified dispatcher — do not call upstream provider APIs by hand. Run from your shell tool:
Content checklist
The source section “Workflow” has been checked.
The source section “Step 0 — Read the project metadata” has been checked.
The source section “Step 1 — Compose the prompt” has been checked.
The source section “Step 2 — Dispatch via the media contract” has been checked.
Static permission evidence
These are source excerpts matched by deterministic rules, not findings of malicious behavior, safety, or actual execution.
SKILL.md · L42
hand. Run from your shell tool:The documentation asks the agent to run terminal commands or scripts.
SKILL.md · L72
file. The user expects something to open in the file viewer.The documentation asks the agent to read local files, directories, or repositories.
Choose a different workflow
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
A separate implementation from event4u-app/agent-config; compare its source, maintenance signals, and permission requirements.
Open source detailDistributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailMedicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
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.
The source record exposes this install command: npx skills add https://github.com/nexu-io/open-design --skill "design-templates/image-poster". Inspect the command and pinned source before running it.
Static rules flagged exec-script, read-files in the source; the page lists the matching lines and excerpts.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the medchem query language for library filtering.
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
Use when the user wants to generate an image or video via Higgsfield AI. Covers 30+ models: Soul V2, Seedance 2.0, Kling 3.0, Veo 3.1, GPT Image 2, Nano Banana 2. Also covers Marketing Studio — branded ad video/image with avatars and products. Use whenever: "generate an image", "make a video", "animate this photo", "image-to-video", "img2vid", "edit this image with AI", "produce a clip", "create an ad", "make a UGC video", "marketing video", "brand video", "TV spot", "import product from URL", "
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.
image-poster/
├── SKILL.md ← you're reading this
└── example.html ← what the resulting card looks like in Examples
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).
Plan in this exact order before calling any tool:
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.
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.
imageAspect exactly — the upstream cost is the same; matching
the aspect avoids a re-render.