Master prompt
GPT-Image-1 — Canada CRS scorecard infographic
Service-specific visual metaphor for Canada Express Entry: an illustrated CRS scorecard breaking down the 1200-point system into age / education / language / experience / spouse / additional buckets.
ImageGPT-Image-1CAMarketingInfographic
**TARGET MODEL: ChatGPT Images 2.0 (gpt-image-2, April 2026 release).** Use 2.0-specific capabilities:
- Embed exact text strings — 99% accuracy English, 90%+ Hindi/Punjabi/Bengali/Arabic/CJK. Spell every word verbatim in the prompt; the model will render it as typed.
- Let 2.0 plan composition first (the model uses an internal reasoning step). Specify spatial layout in plain language ("primary subject left-third, accent right-third, headline top-center").
- Request 2K (2048x2048 or 2048x1152) when the output is for web hero / OG / LinkedIn — use 1024px square only for thumbnails.
- For carousel / slide-deck use cases, ask for a coherent SET of up to 8 images in one call.
- If multilingual diaspora copy is needed (Punjabi for Brampton, Hindi for North-India market, Tamil for SG diaspora), specify the EXACT script + transliteration to lock the rendering.
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Generate a clean illustrated CRS scorecard infographic at 1:1 (1024x1024 px target) explaining the 1200-point Canada Express Entry comprehensive ranking system.
Composition:
- Background: warm off-white #F6F4EF with subtle 2% paper-grain.
- Top 15%: header strip with the eyebrow "COMPREHENSIVE RANKING SYSTEM" in small-caps Geist sans #1E3A5F at 70% opacity, and the headline "CRS at a glance" in Fraunces serif #1E3A5F xxl.
- Center 70%: a stacked horizontal bar chart, six rows top-to-bottom. Each row shows the maximum points available in each CRS bucket:
Row 1 - "Age" - bar fill to 110 of 1200 in #5E54FF.
Row 2 - "Education" - bar fill to 150 of 1200 in #5E54FF.
Row 3 - "Language (CLB)" - bar fill to 160 of 1200 in #5E54FF.
Row 4 - "Work experience" - bar fill to 80 of 1200 in #5E54FF.
Row 5 - "Spouse / common-law" - bar fill to 40 of 1200 in #5E54FF.
Row 6 - "Additional (PNP, job offer, French)" - bar fill to 600 of 1200 in #F28C28 (the orange highlights the leverage row).
Each row: label on the left in #1E3A5F Geist sans (14pt), bar in the center, numeric points-out-of-1200 label on the right in Geist Mono #1E3A5F.
Subtle horizontal grid lines in #E5E7EB at 0 / 300 / 600 / 900 / 1200 marks across all rows.
- Bottom 15%: a single-line takeaway in #1E3A5F italic Fraunces serif: "Additional points are the leverage point — PNP nomination alone adds 600."
- Bottom-left watermark: "[FIRM_NAME]" tiny serif italic in #1E3A5F at 50% opacity.
- Bottom-right: "DRAFT" stamp #F28C28 rotated -12 degrees, ~50px tall.
Color palette (strict):
- Off-white #F6F4EF (background)
- Navy #1E3A5F (type, axis labels)
- Indigo #5E54FF (rows 1-5 bars)
- Draft orange #F28C28 (row 6 highlight + DRAFT stamp)
Typography:
- Geist sans for labels, Geist Mono for numbers, Fraunces serif for the headline and takeaway.
Style:
- Clean data-viz aesthetic, FT-Graphics-team / Pudding sensibility.
- Flat. No 3D, no gradients on the bars themselves, no shadows.
- Numbers must render correctly - GPT-Image-1 should spell out digits literally.
Negatives:
- No maple leaf, no Canadian flag, no IRCC logo or insignia.
- No stock-photo people, no human figures at all.
- No fake/invented numbers - use 110, 150, 160, 80, 40, 600 exactly as specified.
- No gold/red palette dominance.
- No AI-art tells (melted text, extra grid lines that don't align).
GPT-Image-1 specific tips: state row order top-to-bottom explicitly. State each numeric value literally so the model can render it. Verify the row 6 highlight is the only orange element.
DRAFT - for consultant/firm brand review. Verify generated image does NOT include trademarked logos, real-person likenesses, or any government-issued seal that could be mistaken for an official document. Brand colors must align with firm guidelines. Generated images are for marketing only - never use to imply official endorsement.Unlock the vault to see the full prompt