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last30days-research

Research any topic across the last 30 days using Reddit, Twitter, YouTube, Hacker News, web search, and news sources through SandBase. Use when asked for recent trends, launch reactions, competitor activity, person/company profiles, or current event analysis.

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包含的文件(2)

  • SKILL.md2.6 KB
  • references/sandbase-api-map.md1.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Last 30 Days Research

Comprehensive recent-history research across multiple platforms through SandBase. Aggregate the last 30 days of activity on a topic from Reddit, Twitter, YouTube, news, and web search. Read the API map before selecting a capability.

Call SandBase capabilities

Use the capability identifiers below as discovery hints, not MCP tool names. Find the matching endpoint with sandbase_discover(q: "<provider and capability>"); use its returned name in sandbase_inspect(name: "<returned name>"). Read inputSchema, pricing, and execute_as, then call sandbase_run using execute_as.arguments.name and schema-defined arguments. If a run_id is returned, poll sandbase_run_get(run_id: "<returned run_id>") within the task budget until completed or failed; report pending or failed runs without resubmitting them automatically.

Operating principles

  • Cast a wide net: query at least 3-4 platforms for comprehensive coverage.
  • Weight recency — more recent signals are more relevant.
  • Note platform bias: Reddit skews technical, Twitter skews real-time, YouTube skews educational.
  • Cross-reference findings for confidence scoring.
  • Report timeline: when did mentions spike or change tone?

Workflow

1. Web and news

Use tavily_search with days: 30 and topic: "news" for news coverage. Use google_news_bulk_articles for comprehensive news articles. Use exa_search with date filters for high-quality web sources.

2. Social platforms

Use twitter_web_search_timeline for Twitter/X mentions and discussions. Use reddit_app_dynamic_search for Reddit discussions. Use youtube_web_v2_general_search for relevant YouTube content.

3. Synthesize timeline

Cluster findings by week, identify spikes, track sentiment changes.

Output

Return: timeline of activity, platform-by-platform summary, key events/milestones, sentiment trend, influencer involvement, and gaps/blind spots.

Example tasks

  • "What's happened with [topic] in the last 30 days across the internet?"
  • "Track [product launch] reception across all platforms over the past month."
  • "How has discussion about [company] evolved on Twitter and Reddit recently?"
  • "Find all significant mentions of [person] in the last 30 days."
  • "What's the recent trend around [technology]? Combine news, social, and community data."

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