parallel-web/parallel-agent-skills▌

Exhaustive research with configurable depth, latency, and cost trade-offs for complex topics. \n \n Three processor tiers (pro-fast, ultra-fast, ultra) ranging from 30 seconds to 25 minutes, with cost scaling from 1x to 3x baseline \n Asynchronous execution with polling: kick off research instantly, monitor progress via URL, retrieve results when ready without blocking \n Outputs formatted markdown report and JSON metadata; executive summary printed to stdout for quick overview \n Designed for e

Bulk enrichment of company, people, or product data with web-sourced fields like CEO names, funding, and contact info. \n \n Accepts inline JSON data or CSV files; outputs enriched results to CSV \n Runs asynchronously with progress tracking via monitoring URL and polling commands \n Requires parallel-cli tool and internet access; handles large datasets with configurable timeouts \n Supports flexible field requests through natural language intent descriptions (e.g., \"CEO name and founding year\

Installs and authenticates the Parallel CLI for agent integration. \n \n Provides two installation methods: automated install script or pip-based installation via pipx \n Includes authentication setup via parallel-cli login and verification commands to confirm successful installation \n Requires PATH configuration if the CLI binary is not automatically discoverable after installation \n

Retrieve completed research task results using a run ID. \n \n Polls research task status and returns results in JSON format via the parallel-cli tool \n Requires a valid run ID as input; displays setup instructions if the CLI is not installed \n Presents output in a clear, organized format for easy consumption \n

Extract content from multiple URLs in parallel, token-efficiently. \n \n Handles webpages, articles, PDFs, and JavaScript-heavy sites with a single command \n Runs in a forked context to minimize token overhead compared to built-in WebFetch \n Supports batch extraction of multiple URLs with optional focus objectives \n Requires parallel-cli installation and authentication; outputs extracted content as markdown to a local file for follow-up queries \n

Fast web search for current information, research, and fact-finding across the internet. \n \n Executes single objective-based queries or multiple keyword searches in parallel, returning up to 10 results with excerpts and metadata \n Supports time-sensitive filtering via --after-date and domain-specific searches with --include-domains \n Outputs structured JSON with titles, URLs, publish dates, and excerpts for easy parsing and follow-up queries \n Requires inline citations for every claim using

Check the status of a running research task by its run ID. \n \n Queries research task status using the Parallel CLI with JSON output formatting \n Requires the Parallel CLI to be installed; directs users to /parallel:setup if unavailable \n Accepts a run ID as the sole argument to identify which task to monitor \n