skills/last-30-days-research/SKILL.md
Multi-platform research skill that gathers recent (last 30 days) opinions, sentiment, and signal on any topic from Reddit, X/Twitter, and the web. Cuts through SEO-stuffed results to surface what real people are actually saying.
npx skillsauth add mohitagw15856/pm-claude-skills last-30-days-researchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
| Input | Required | Notes | |-------|----------|-------| | Topic | Yes | Tool, trend, feature, product, event, company — anything with a name | | Date scope | No | Defaults to last 30 days. Can override to last 7 days or last 90 days | | Angle | No | e.g. "focus on developer sentiment" or "looking for pricing complaints specifically" |
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.
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.
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").
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).
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.
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.
Populate each section of the output structure. Follow these rules:
Before outputting the report, verify:
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