> ## Documentation Index
> Fetch the complete documentation index at: https://docs.endprompt.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Use Cases
> Real-world examples of Endprompt in action
Explore common use cases and get inspired for your own implementations.
## Content & Marketing
### Email Subject Line Generator
Generate compelling email subject lines from email content.
**Input Schema:**
* `email_body` (string, required)
* `tone` (string: professional, casual, urgent)
* `count` (integer, default: 5)
**Prompt:**
```liquid theme={null}
Generate {{ inputs.count }} email subject lines for the following email.
Tone: {{ inputs.tone | default: "professional" }}
Email content:
{{ inputs.email_body | truncate: 2000 }}
Requirements:
- Under 60 characters each
- Create curiosity or urgency
- No clickbait or misleading content
Return JSON: {"subjects": ["subject1", "subject2", ...]}
```
### Blog Post Outliner
Create structured outlines for blog posts.
**Input Schema:**
* `topic` (string, required)
* `audience` (string, required)
* `word_count_target` (integer)
**Prompt:**
```liquid theme={null}
Create a detailed outline for a blog post.
Topic: {{ inputs.topic }}
Target audience: {{ inputs.audience }}
Target length: {{ inputs.word_count_target | default: 1500 }} words
Include:
- Engaging title options (3)
- Introduction hook
- 4-6 main sections with subpoints
- Conclusion with CTA
- SEO keywords to target
Return a structured JSON outline.
```
***
## Customer Support
### Ticket Classifier
Automatically categorize and prioritize support tickets.
**Input Schema:**
* `ticket_subject` (string, required)
* `ticket_body` (string, required)
* `categories` (array of strings)
**Prompt:**
```liquid theme={null}
Classify this support ticket.
Subject: {{ inputs.ticket_subject }}
Body: {{ inputs.ticket_body }}
Available categories:
{% for cat in inputs.categories %}
- {{ cat }}
{% endfor %}
Determine:
1. Primary category
2. Priority (low, medium, high, urgent)
3. Sentiment (positive, neutral, negative)
4. Suggested response type (template, custom, escalation)
Return JSON with your classification.
```
### Response Drafter
Draft customer support responses.
**Input Schema:**
* `customer_message` (string, required)
* `customer_name` (string)
* `issue_type` (string)
* `tone` (string)
**Prompt:**
```liquid theme={null}
Draft a support response for this customer inquiry.
Customer: {{ inputs.customer_name | default: "Customer" }}
Issue type: {{ inputs.issue_type }}
Tone: {{ inputs.tone | default: "friendly and professional" }}
Customer message:
{{ inputs.customer_message }}
Guidelines:
- Acknowledge their concern
- Provide clear next steps
- Offer additional help
- Keep under 200 words
{% include 'support-signature' %}
```
***
## Data Processing
### Entity Extractor
Extract structured data from unstructured text.
**Input Schema:**
* `text` (string, required)
* `entity_types` (array: person, company, date, location, amount)
**Prompt:**
```liquid theme={null}
Extract entities from the following text.
Entity types to find:
{% for type in inputs.entity_types %}
- {{ type }}
{% endfor %}
Text:
{{ inputs.text }}
For each entity found, include:
- type: the entity type
- value: the extracted text
- normalized: standardized format (dates as ISO, amounts with currency)
- confidence: 0.0 to 1.0
Return: {"entities": [...]}
```
### Document Summarizer
Summarize documents with configurable detail levels.
**Input Schema:**
* `document` (string, required)
* `format` (string: bullets, paragraph, executive)
* `max_length` (integer)
**Prompt:**
```liquid theme={null}
Summarize this document.
Format: {{ inputs.format | default: "bullets" }}
Max length: {{ inputs.max_length | default: 200 }} words
{% case inputs.format %}
{% when "executive" %}
Write for a busy executive: key findings, implications, recommended actions.
{% when "bullets" %}
Use bullet points for easy scanning.
{% when "paragraph" %}
Write a flowing paragraph summary.
{% endcase %}
Document:
{{ inputs.document | truncate: 15000 }}
{% include 'json-output-instructions' %}
```
***
## E-Commerce
### Product Description Writer
Generate compelling product descriptions.
**Input Schema:**
* `product_name` (string, required)
* `features` (array, required)
* `target_audience` (string)
* `tone` (string)
**Prompt:**
```liquid theme={null}
Write a product description for:
Product: {{ inputs.product_name }}
Key features:
{% for feature in inputs.features %}
- {{ feature }}
{% endfor %}
Target audience: {{ inputs.target_audience | default: "general consumers" }}
Tone: {{ inputs.tone | default: "persuasive but honest" }}
Include:
- Attention-grabbing headline
- 2-3 paragraph description
- Bullet point benefits (5)
- Call to action
Return structured JSON with each section.
```
### Review Analyzer
Analyze customer reviews for insights.
**Input Schema:**
* `reviews` (array of strings, required)
* `product_name` (string)
**Prompt:**
```liquid theme={null}
Analyze these customer reviews for {{ inputs.product_name | default: "this product" }}.
Reviews:
{% for review in inputs.reviews %}
---
{{ review }}
{% endfor %}
---
Provide:
1. Overall sentiment breakdown (% positive/neutral/negative)
2. Top 5 praised features
3. Top 5 complaints
4. Common suggestions for improvement
5. Key quotes (positive and negative)
Return comprehensive JSON analysis.
```
***
## Development Tools
### Code Explainer
Explain code in plain language.
**Input Schema:**
* `code` (string, required)
* `language` (string)
* `audience` (string: beginner, intermediate, expert)
**Prompt:**
```text theme={null}
Explain this code to a developer.
[The user's code is inserted here via inputs.code]
Include:
- What the code does at a high level
- Step-by-step walkthrough
- Key concepts used
- Potential improvements
- Definitions of technical terms for beginners
Return structured JSON explanation.
```
### API Documentation Generator
Generate API documentation from code.
**Input Schema:**
* `code` (string, required)
* `framework` (string)
**Prompt:**
```text theme={null}
Generate API documentation for this API endpoint.
[The user's code is inserted here via inputs.code]
Document:
- Endpoint URL and method
- Description
- Request parameters with types and requirements
- Request body schema
- Response schema
- Example request and response
- Error responses
Return in OpenAPI-compatible JSON format.
```
***
## Getting Started with These Use Cases
1. **Pick a use case** that matches your needs
2. **Create an endpoint** with the suggested input schema
3. **Copy the prompt** and customize for your domain
4. **Test thoroughly** with real-world examples
5. **Iterate** based on results
***
## Image & Vision
### Product Image Generator
Generate marketing images from product descriptions.
**Input Schema:**
* `product_name` (string, required)
* `style` (string: minimalist, lifestyle, studio)
* `background` (string)
**Model:** gpt-image-1
**Custom Parameters:**
```json theme={null}
[
{ "name": "size", "value": "1024x1536" },
{ "name": "quality", "value": "high" }
]
```
**Prompt:**
```liquid theme={null}
A professional product photography shot of {{ inputs.product_name }}.
Style: {{ inputs.style | default: "minimalist" }}.
Background: {{ inputs.background | default: "clean white studio" }}.
High resolution, commercial quality, centered composition.
```
**Output Schema:**
* `generated_image` (image)
### Image Analyzer
Extract structured data from product photos.
**Input Schema:**
* `photo` (image, required)
* `categories` (array of strings)
**Model:** GPT-4o (vision-capable)
**Prompt:**
```liquid theme={null}
Analyze this product image and extract:
1. A detailed description (2-3 sentences)
2. Up to 10 relevant tags
3. Dominant colors as hex values
4. Suggested product category
{% if inputs.categories %}
Choose the category from: {{ inputs.categories | join: ", " }}
{% endif %}
Return structured JSON.
```
**Output Schema:**
* `description` (string)
* `tags` (array)
* `colors` (array)
* `category` (string)
### Image Editor
Modify existing images based on text instructions.
**Input Schema:**
* `reference_image` (image, required)
* `edit_instructions` (string, required)
**Model:** gpt-image-1
**Prompt:**
```liquid theme={null}
{{ inputs.edit_instructions }}
```
**Output Schema:**
* `edited_image` (image)
When input images are provided with an image output field, Endprompt automatically routes to the provider's editing API. See the [Image Generation & Vision](/guides/image-generation) guide for details.
***
These examples are starting points. Customize the prompts, schemas, and models based on your specific requirements.
## Need More Examples?
Browse community-contributed templates
Request custom use case guidance