AI prompt for an Amazon or Shopify product listing
Prompt to write a product listing for Amazon or Shopify in English: title, 5 bullet points and description, from raw product specs.
Template
Write a product listing for an online store ({{marketplace}}).
Product: {{product}}
Specs: {{specs}}
Target customer: {{audience}}
Return, in American English:
1. A title under 150 characters, main keyword first, no promotional claims ("best", "#1")
2. Five bullet points, each starting with a short benefit in capitals followed by the supporting spec
3. A 150 to 200 word description in plain, concrete language
4. Five search terms customers would type, comma-separated
Use U.S. units (inches, pounds, °F). Do not invent any feature that is not in the specs.Variables
Estimated cost
Input tokens per call : ≈ 243
| Model | Per call | Per 1,000 calls |
|---|---|---|
| Mistral Large · Mistral AI | €0.00011 | €0.11 |
| DeepSeek Flash · DeepSeek | €0.00006 | €0.06 |
| DeepSeek V4 Pro · DeepSeek | €0.00028 | €0.28 |
| GPT-6 Luna · OpenAI | €0.00002 | €0.02 |
| GPT-6 Sol · OpenAI | €0.00043 | €0.43 |
| Claude Sonnet 5.5 · Anthropic | €0.00043 | €0.43 |
| Claude Opus 5.5 · Anthropic | €0.00086 | €0.86 |
| Self-hosted open-source model (Ollama, vLLM) | €0 in API fees (server cost only) | |
Input cost only, excluding the model's answer. Providers' public standard prices (Mistral AI, DeepSeek, OpenAI, Anthropic) converted from USD to euros at the ECB rate of September 29, 2026. Estimate: 1 token ≈ 3.6 characters.
Common to all 3 regions
Created by the author, no outside source.
Commercial use allowed · credit the author · changes allowed.
Text or data only: no access to files, network or commands.
Hosted in France (Scaleway, Paris). No transfer outside the EU.
European Union · 5/5
No personal data.
No training data: no summary required.
United States · 5/5
No personal data.
No training data: no documentation to publish.
China · 5/5
No personal data.
No training data; AI-generated content published in China must be labelled (2025).
Indicative summary as of 30/09/2026, not a legal certification. Method and sources →
Pin a version in your code
import contexte p = contexte.load("contextetech/amazon-shopify-product-listing", version=1) print(p.fill(marketplace="…", product="…", specs="…", audience="…"))
$ contexte get vqf4s1#v1 Statistics
Likes : 0 · Comments : 0
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- Identifier
- contextetech--amazon-shopify-product-listing
- Type
- Prompts
- File
- amazon-shopify-product-listing.json
- Format
- JSON (application/json)
- Size
- 1,029 bytes (1 KB)
- Encoding
- UTF-8
- Estimated tokens
- ≈ 286
- Language
- English
- License
- MIT
- Commercial use
- Allowed
- Personal data
- None
- Version
- 1.0
- Published on
- October 2, 2026 at 9:54 PM
- Updated on
- October 2, 2026 at 9:54 PM
- Storage
- in database
- Uses
- 0
- Likes
- 0
Python contexte
$ pip install contexte import contexte p = contexte.load("contextetech/amazon-shopify-product-listing") print(p.fill(marketplace="…", product="…", specs="…", audience="…"))
$ contexte get vqf4s1 amazon-shopify-product-listing.json
{
"format": "contextec/prompt/v1",
"id": "contextetech/amazon-shopify-product-listing",
"description": "Prompt to write a product listing for Amazon or Shopify in English: title, 5 bullet points and description, from raw product specs.",
"tags": [
"ecommerce",
"copywriting",
"seo"
],
"license": "MIT",
"language": "en",
"template": "Write a product listing for an online store ({{marketplace}}).\n\nProduct: {{product}}\nSpecs: {{specs}}\nTarget customer: {{audience}}\n\nReturn, in American English:\n1. A title under 150 characters, main keyword first, no promotional claims (\"best\", \"#1\")\n2. Five bullet points, each starting with a short benefit in capitals followed by the supporting spec\n3. A 150 to 200 word description in plain, concrete language\n4. Five search terms customers would type, comma-separated\n\nUse U.S. units (inches, pounds, °F). Do not invent any feature that is not in the specs.",
"variables": [
"marketplace",
"product",
"specs",
"audience"
]
}
Community
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