Last 30 Days

Cluster Reddit, X, Hacker News, and web sentiment into sourced narrative reports.

6|2|Updated May 21, 2026
One-click install
npx skills add https://github.com/anajuliabit/aeon --skill last-30-days-anajuliabit
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Last 30 Days
Source: https://github.com/anajuliabit/aeon/tree/main/skills/last30
Command: npx skills add https://github.com/anajuliabit/aeon --skill last-30-days-anajuliabit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

It solves the problem of turning scattered social chatter across multiple platforms into coherent, decision-ready narrative insight for a specific topic over the last 30 days.

Core Features & Use Cases

  • Narrative-first cross-platform research: clusters what people are saying across Reddit, X, HN, Polymarket, and the web into narrative groupings rather than platform-by-platform recaps.
  • Disagreement as a signal: highlights where platforms diverge in sentiment so you can spot actionable contradictions (e.g., Reddit bearish vs X bullish on the same story).
  • Snapshot comparison (What Changed): compares the current window to a prior snapshot and flags NEW, FADED, FLIPPED, or HEATING narratives to show trend movement rather than static summaries.
  • Falsifiable, sourced reporting: requires every quote/stat to trace back to fetched sources and omits sections (like prediction markets) when no matches are found.

Quick Start

Ask for a narrative research report by setting var to your topic, for example: run Last 30 Days with var="your topic".

Frequently Asked Questions about Last 30 Days

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate cross-platform narrative research from social media and web sources?

Cross-platform narrative research is generated by parsing a specific topic, extracting data over a 30-day window from Reddit, X, Hacker News, prediction markets, and the web, and clustering the findings into cohesive narrative groupings using anchor-token overlap.

Can I compare current social sentiment trends against a previous snapshot?

You can compare current social sentiment trends against a prior snapshot to identify trend movements, flagging narratives as NEW, FADED, FLIPPED, or HEATING to show how conversations have changed rather than providing a static summary.

How does cross-platform sentiment divergence detect disagreements between Reddit and X?

Cross-platform sentiment divergence detects disagreements by mapping sentiment across platforms and highlighting actionable contradictions, such as Reddit being bearish while X is bullish on the exact same narrative topic.

How do I cluster recurring themes from web monitoring into research briefings?

Recurring themes from web monitoring are clustered into research briefings by deduplicating fetched sources, applying anchor-token overlap to group related discussions, and emitting a sourced Markdown report with structured sentiment mapping.

What happens to my narrative research report if no prediction market data is found?

If no prediction market data is found for your topic, the narrative research report omits the prediction markets section entirely, ensuring that all reporting remains falsifiable and strictly traces back to fetched sources.

Do I need to provide a specific topic parameter to start narrative clustering?

You need to provide a specific topic parameter to start narrative clustering, which enforces a 30-day date-window extraction to ensure the research accurately reflects what people are saying about that subject recently.