parallel-web-extract
Extract content from multiple URLs in parallel, token-efficiently.
Works with
What it does
Handles webpages, articles, PDFs, and JavaScript-heavy sites with a single command
Runs in a forked context to minimize token overhead compared to built-in WebFetch
Supports batch extraction of multiple URLs with optional focus objectives
Requires parallel-cli installation and authentication; outputs extracted content as markdown to a local file for follow-up queries
Installation Guide
How to use parallel-web-extract on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- βΊCursor installed and configured on your machine
- βΊNode.js 16+ with npm β verify with
node --version - βΊActive project directory where you want to add
parallel-web-extract
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches parallel-web-extract from parallel-web/parallel-agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate parallel-web-extract. Access via /parallel-web-extract in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
URL Extraction
Extract content from: $ARGUMENTS
Command
Choose a short, descriptive filename based on the URL or content (e.g., vespa-docs, react-hooks-api). Use lowercase with hyphens, no spaces.
parallel-cli extract "$ARGUMENTS" --json -o "/tmp/$FILENAME.md"
Options if needed:
--objective "focus area"to focus on specific content
Response format
Return content as:
Then the extracted content verbatim, with these rules:
- Keep content verbatim - do not paraphrase or summarize
- Parse lists exhaustively - extract EVERY numbered/bulleted item
- Strip only obvious noise: nav menus, footers, ads
- Preserve all facts, names, numbers, dates, quotes
After the response, mention the output file path (/tmp/$FILENAME.md) so the user knows it's available for follow-up questions.
Setup
If parallel-cli is not found, install and authenticate:
curl -fsSL https://parallel.ai/install.sh | bash
If unable to install that way, install via pipx instead:
pipx install "parallel-web-tools[cli]"
pipx ensurepath
Then authenticate:
parallel-cli login
Or set an API key: export PARALLEL_API_KEY="your-key"
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale