riveter

Web scraping with structured data extraction - define your output schema

9 stars

Best use case

riveter is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Web scraping with structured data extraction - define your output schema

Teams using riveter 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

$curl -o ~/.claude/skills/orthogonal-riveter/SKILL.md --create-dirs "https://raw.githubusercontent.com/orthogonal-sh/skills/main/skills/orthogonal-riveter/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/orthogonal-riveter/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How riveter Compares

Feature / AgentriveterStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Web scraping with structured data extraction - define your output schema

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

# Riveter - Structured Web Scraping

Scrape web pages and extract data into your defined structure.

## Capabilities

- **Scrape**: Scrape a webpage and return the text content
- **Run**: Copy link Define the structure of your output directly in the API request
- **Run data**: Retrieve the processed data from a completed project run (free)
- **Run status**: Check the current status of a project run (free)
- **Stop run**: Stop a currently running project (free)

## Usage

### Scrape
Scrape a webpage and return the text content. This endpoint allows you to extract text content from any public webpage.

Parameters:
- url* (string) - Example: "https://example.com"
- proxy_country_code (string) - Optional two-character country code for proxy (e.g., 'us', 'gb', 'de')
- skip_cache (boolean) - Default: false. Set to true to bypass cache and always fetch fresh content

```bash
orth api run riveter /v1/scrape --body '{"url": "https://example.com/article"}'
```

### Run
Copy link Define the structure of your output directly in the API request. This endpoint allows you to define both your input data and output configuration in a single request.

Parameters:
- input* (object) - The input object contains your source data:  Keys are column/attribute names Values are arrays of strings (all arrays must be the same length) Maximum 1000 rows per request
- output* (object) - The output object defines what data you want to extract:  Keys are the names of attributes you want to extract Each attribute requires: prompt: Instructions for finding/extracting this data contexts: Array of input or other output attribute names this depends on. Optional Output Configuration Each output attribute can optionally include:  format: Data type ('number', 'json', 'url', 'text', 'email', 'tag', 'date', 'boolean') format_details: Format-specific configuration (varies by format type). For json format, you can provide either a description (string) or a schema (JSON Schema object) or both. tools: Array of tools to use (['web_search', 'web_scrape', 'query_pdf', 'query_image']) max_tool_calls: Number of tool calls allowed (0-10) run_when: When to run this extraction ('always', 'any_filled', 'all_filled')
- run_key (string) - Custom identifier for this run (optional, will be generated if not provided)

```bash
orth api run riveter /v1/run --body '{
  "input": {
    "urls": ["https://example.com/products"]
  },
  "output": {
    "name": {"prompt": "Product name", "contexts": ["urls"]},
    "price": {"prompt": "Product price", "contexts": ["urls"], "format": "number"}
  }
}'
```

### Run data (free)
Retrieve the processed data from a completed project run

Parameters:
- run_key* (string) - The run key (UUID) of the project run to retrieve data for

```bash
orth api run riveter /v1/run_data --query 'run_key=abc123'
```

### Run status (free)
Check the current status of a project run

Parameters:
- run_key* (string) - The run key (UUID) of the project run to check

```bash
orth api run riveter /v1/run_status --query 'run_key=abc123'
```

### Stop run (free)
Stop a currently running project. This will halt all processing and mark the run as stopped. Behavior:  If the run is already stopped or success, returns success with current status. If the run is in progress, stops all pending cells and marks the run as stopped.  Stopped runs cannot be resumed

Parameters:
- run_key* (string) - The run key (UUID) of the project run to stop

```bash
orth api run riveter /v1/stop_run --query 'run_key=abc123'
```

## Use Cases

1. **E-commerce Scraping**: Extract product data in consistent format
2. **Job Listings**: Gather job postings with structured fields
3. **News Aggregation**: Extract articles with title, date, content
4. **Price Monitoring**: Track prices across competitor sites

## Discover More

For full endpoint details and parameters:

```bash
orth api show riveter              # List all endpoints
orth api show riveter /v1/scrape   # Get endpoint details
```

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