Last 30 Days Research

Last 30 Days Research

The Problem

Googling gives SEO-stuffed "best of" lists written six months ago by someone who has never used the thing. Real honest takes live on Reddit threads, X replies, and niche communities — but chasing them across platforms eats your afternoon. This skill does the chase for you.

Required Inputs

Output Structure

The output is a structured research report with the following sections, delivered in this exact order:

## Last 30 Days Research: [Topic]
Research window: [Date 30 days ago] → [Today's date]

---

## What People Agree On
[Consensus points that appear across multiple platforms — most reliable signal]

## Where People Disagree
[Active debates, contrasting views — include which side has more weight]

## Pain Points That Keep Coming Up
[Recurring complaints and frustrations — strongest signal of real problems]

## Positive Signals
[What people genuinely praise — not PR, but unprompted appreciation]

## Most Interesting Takes
[Contrarian, unexpected, or surprisingly insightful comments worth noting]

## Sources
[Links to the most useful threads/posts found — 5–10 links with brief labels]

## Signal Confidence
[High / Medium / Low — with a one-line rationale based on data volume and consistency]

Each section should contain substantive content, not placeholders. If a section has no findings (e.g. no positive signals found), state that explicitly rather than leaving it empty or fabricating content.

Instructions for Claude

Step 1 — Calculate the date window

Determine today's date and subtract 30 days to get the research start date. Format: YYYY-MM-DD. Use these dates explicitly in every search query.

Step 2 — Reddit search

Run at least three web searches targeting Reddit:

site:reddit.com "[topic]" after:[30-days-ago-date]
site:reddit.com "[topic]" 2025
reddit.com "[topic]" discussion OR thread OR comments

For each result: read the thread title, top-level comments, and any highly-upvoted replies. Record the key claims and the URL.

If the topic has common synonyms or abbreviations, run additional searches with those (e.g. "Claude Code" and "claude.code" and "Anthropic coding tool").

Step 3 — X/Twitter search

Run at least two web searches targeting X:

site:twitter.com OR site:x.com "[topic]" after:[30-days-ago-date]
"[topic]" site:x.com -is:retweet

Note: X search via web has limitations. If results are sparse, supplement with searches for specific accounts known to discuss the topic area (e.g. tech journalists, domain experts).

Step 4 — Broader web search

Run at least two broader searches for articles, blog posts, and commentary:

"[topic]" review OR opinion OR experience [month] [year]
"[topic]" vs OR alternative OR comparison [month] [year]

Target sources: Hacker News, Substack, dev.to, personal blogs, product communities. Avoid press releases and vendor-authored content.

Step 5 — Cross-platform corroboration check

Before writing the report, review everything collected and apply the corroboration rule:

When the same point appears on both Reddit and X independently, treat it as strong signal — it's likely true.

A point mentioned only once on one platform is a data point, not a finding. Weight your sections accordingly.

Step 6 — Write the report

Populate each section of the output structure. Follow these rules:

• What People Agree On: Only include points you saw on 2+ platforms or in multiple independent threads. These are your most reliable findings.
• Where People Disagree: Name the sides. "Some say X, others say Y — and the X camp seems louder based on upvote counts / engagement."
• Pain Points: Be specific. "Performance issues" is weak. "Cold start times over 4 seconds on the free tier" is useful.
• Positive Signals: Must be unprompted praise, not from product marketing or sponsored content.
• Most Interesting Takes: At least 2, maximum 5. Quote or closely paraphrase where possible.
• Sources: Include the actual URLs. Label each one briefly (e.g. "Reddit thread: 'Has anyone switched from X to Y?'").
• Signal Confidence: Rate High/Medium/Low based on:
  • High = 10+ sources, consistent signal across platforms
  • Medium = 5–10 sources, some inconsistency
  • Low = fewer than 5 sources, or highly fragmented signal