orthogonal-image-analyzer
Analyze images with AI - extract text, describe content, detect objects
Best use case
orthogonal-image-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze images with AI - extract text, describe content, detect objects
Teams using orthogonal-image-analyzer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/orthogonal-image-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orthogonal-image-analyzer Compares
| Feature / Agent | orthogonal-image-analyzer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze images with AI - extract text, describe content, detect objects
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Image Analyzer - AI Image Analysis
## Setup
Read your credentials from ~/.gooseworks/credentials.json:
```bash
export GOOSEWORKS_API_KEY=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json'))['api_key'])")
export GOOSEWORKS_API_BASE=$(python3 -c "import json;print(json.load(open('$HOME/.gooseworks/credentials.json')).get('api_base','https://api.gooseworks.ai'))")
```
If ~/.gooseworks/credentials.json does not exist, tell the user to run: `npx gooseworks login`
All endpoints use Bearer auth: `-H "Authorization: Bearer $GOOSEWORKS_API_KEY"`
Analyze images to extract text, describe content, and detect objects using AI.
## Workflow
### Step 1: Get Image from URL
Fetch image content:
```bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"linkup","path":"/fetch","body":{"url":"https://example.com/image.jpg"}}'
```
### Step 2: Extract Text (OCR)
Use AI to extract text from images:
```bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"scrapegraph","path":"/v1/smartscraper"}'
"website_url": "https://example.com/screenshot.png",
"user_prompt": "Extract all visible text from this image"
}'
```
### Step 3: Extract Structured Data
Get specific data from images:
```bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"riveter","path":"/v1/run"}'
"input": {
"urls": ["https://example.com/receipt.jpg"]
},
"output": {
"store_name": {"prompt": "Store name", "contexts": ["urls"]},
"date": {"prompt": "Date", "contexts": ["urls"]},
"items": {"prompt": "Items with names and prices", "contexts": ["urls"]},
"total": {"prompt": "Total amount", "contexts": ["urls"]}
}
}'
```
### Step 4: Capture Website Screenshots
Get screenshots of web pages:
```bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"brand-dev","path":"/v1/brand/screenshot","query":{"domain":"stripe.com"}}'
```
## Example Usage
```bash
# Extract receipt data
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"scrapegraph","path":"/v1/smartscraper"}'
"website_url": "https://example.com/receipt.jpg",
"user_prompt": "Extract store name, date, all items with prices, and total amount"
}'
# Get website screenshot
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/run \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"api":"brand-dev","path":"/v1/brand/screenshot","query":{"domain":"openai.com"}}'
```
## Tips
- Use clear, high-resolution images
- Specify exact data needed for extraction
- Combine with OCR for text-heavy images
- Use screenshots for website analysis
## Discover More
List all endpoints, or add a path for parameter details:
```bash
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"prompt":"brand-dev API endpoints"}' api show linkup
curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/search \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
-d '{"prompt":"riveter API endpoints"}' api show scrapegraph
```
Example: `curl -s -X POST $GOOSEWORKS_API_BASE/v1/proxy/orthogonal/details \
-H "Authorization: Bearer $GOOSEWORKS_API_KEY" \
-H "Content-Type: application/json" \
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