union-search-skill

Multi-platform search aggregation normalizes results from over 20 sources like Reddit and GitHub into a single JSON structure. This orchestrates platform scripts, enforces standardized outputs, and supports filtering and sorting for consolidated research.

Yes, cross-platform search supports JSON, Markdown, and Text output formats. You can automate the CLI to query multiple platforms, automatically archive the responses, and apply filtering to format the consolidated results as needed.

Bulk image download is supported directly through the union-search workflow. It orchestrates 18 image platforms, aggregates the results into a standardized structure, and enables batch downloading to streamline content discovery.

Multiplatform search aggregation uses dependencies like python-dotenv for environment configuration. You must set up the necessary credentials for platforms like YouTube and Twitter to authenticate requests and retrieve normalized structured outputs.

An automated CLI scales competitive intelligence by orchestrating multiple platform scripts simultaneously. It enforces standardized JSON outputs and archives results automatically, overcoming the limitations of manual cross-platform data collection and formatting.

Pluggable platform adapters depend on external libraries like yt-dlp and feedparser for cross-platform research. Limitations arise if a specific platform changes its API or layout, requiring adapter updates to maintain normalized structured outputs.