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Unified multi-platform search skill that aggregates results from 20+ platforms (GitHub, Reddit, Bilibili, YouTube, Twitter, Chinese platforms) with structured o
Union Search Skill provides a single interface to perform unified searches across more than 20 platforms, including developer sites (GitHub), social media (Reddit, Bilibili, Douyin), video platforms (YouTube), search engines (DuckDuckGo, Bing), and image sources. It standardizes input/output, supports filtering, deduplication, archiving raw responses, and bulk image downloads (with metadata).
Use this skill when you need cross-platform intelligence gathering, content discovery, monitoring mentions across channels, bulk archival of search results, or when working without API keys. Suitable for researchers, threat intelligence, content teams, and engineers building aggregated search tools.
Works with agents that can invoke CLI/python scripts and parse JSON/Markdown outputs (OpenClaw, local Python-based agents, Copilot-style helpers).
Union Search Skill provides a unified CLI for searching 20+ platforms (GitHub, Reddit, Chinese social media, search engines, image search). The SKILL.md is comprehensive and well-organized with detailed usage instructions, but all scripts were absent from the DB record (empty scripts dict), so only static analysis of the markdown was possible. The skill covers a broad range of platforms including niche Chinese services, making it unique in scope, though many platforms require API keys.
SKILL.md is well-structured with good organization (tables, project structure, FAQ). No security concerns in the visible content — no curl|bash, no hardcoded credentials, no destructive commands. However, scripts were not available for review, so security scoring is based purely on SKILL.md content. The skill requires many API credentials for platforms like Google, Tavily, Exa, etc. Code quality is moderate — the markdown instructions are clear but we cannot assess actual script quality. Architecture is decent with proper scripts/ and references/ separation, but the SKILL.md is very long and could benefit from progressive disclosure.
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