Parallel Extract

Extract clean, LLM-ready content from URLs. Handles webpages, articles, PDFs, and JavaScript-heavy sites that need rendering.

When to Use

Trigger this skill when the user asks for:

• "read this URL", "fetch this page", "extract from..."
• "get the content from [URL]"
• "what does this article say?"
• Reading PDFs, JS-heavy pages, or paywalled content
• Getting clean markdown from messy web pages

Use Search to discover; use Extract to read.

Quick Start

parallel-cli extract "https://example.com/article" --json

CLI Reference

Basic Usage

parallel-cli extract "<url>" [options]

Common Flags

| Flag | Description |

|------|-------------|

| --url "" | URL to extract (repeatable, max 10) |

| --objective "" | Focus extraction on specific content |

| --json | Output as JSON |

| --excerpts / --no-excerpts | Include relevant excerpts (default: on) |

| --full-content / --no-full-content | Include full page content |

| --excerpts-max-chars N | Max chars per excerpt |

| --excerpts-max-total-chars N | Max total excerpt chars |

| --full-max-chars N | Max full content chars |

| -o | Save output to file |

Examples

Basic extraction:

parallel-cli extract "https://example.com/article" --json

Focused extraction:

parallel-cli extract "https://example.com/pricing" \
  --objective "pricing tiers and features" \
  --json

Full content for PDFs:

parallel-cli extract "https://example.com/whitepaper.pdf" \
  --full-content \
  --json

Multiple URLs:

parallel-cli extract \
  --url "https://example.com/page1" \
  --url "https://example.com/page2" \
  --json

Default Workflow

1. Search with an objective + keyword queries
2. Inspect titles/URLs/dates; choose the best sources
3. Extract the specific pages you need (top N URLs)
4. Answer using the extracted excerpts/content

Best-Practice Prompting

Objective

When extracting, provide context:

• What specific information you're looking for
• Why you need it (helps focus extraction)

Good: --objective "Find the installation steps and system requirements"

Poor: --objective "Read the page"

Response Format

Returns structured JSON with:

• url — source URL
• title — page title
• excerpts[] — relevant text excerpts (if enabled)
• full_content — complete page content (if enabled)
• publish_date — when available

Output Handling

When turning extracted content into a user-facing answer:

• Keep content verbatim — do not paraphrase unnecessarily
• Extract ALL list items exhaustively
• Strip noise: nav menus, footers, ads, "click here" links
• Preserve all facts, names, numbers, dates, quotes
• Include URL + publish_date for transparency

Running Out of Context?

For long conversations, save results and use sessions_spawn:

parallel-cli extract "<url>" --json -o /tmp/extract-<topic>.json

Then spawn a sub-agent:

{
  "tool": "sessions_spawn",
  "task": "Read /tmp/extract-<topic>.json and summarize the key content.",
  "label": "extract-summary"
}

Error Handling

| Exit Code | Meaning |

|-----------|---------|

| 0 | Success |

| 1 | Unexpected error (network, parse) |

| 2 | Invalid arguments |

| 3 | API error (non-2xx) |

Prerequisites

1. Get an API key at parallel.ai
2. Install the CLI:

curl -fsSL https://parallel.ai/install.sh | bash
export PARALLEL_API_KEY=your-key

References

• API Docs
• Extract API Reference