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Get Started Free →Searches Reddit, X/Twitter, and the broader web for recent opinions, sentiment, and signal on any topic. Use when you need to know what real people are saying about a tool, product, trend, or event in the past 30 days — cutting through SEO content to surface genuine community reaction. Produces a structured report with consensus findings, pain points, positive signals, contrarian takes, source links, and a signal confidence rating.
.claude/skills/mohitagw15856-last-30-days-research/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-20 | ✗→✓ | ▲ Improved | 36% | 0% |
| case-14 | ✓→✗ | ▼ Worse | 9% | 0% |
| case-16 | ✓→✗ | ▼ Worse | 11% | 0% |
| case-17 | ✓→✗ | ▼ Worse | 24% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 32% | 0% |
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 commentsFor 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:retweetNote: 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:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 21,701 | 7,132 | -67% | 1 | 1 | 0% | 3,532 | 2,148 | -39% | 0 | 0 | — |
case-02 | fail→fail | 17,509 | 6,188 | -65% | 1 | 1 | 0% | 2,790 | 2,216 | -21% | 0 | 0 | — |
case-03 | fail→fail | 19,254 | 6,170 | -68% | 1 | 1 | 0% | 3,111 | 2,106 | -32% | 0 | 0 | — |
case-04 | pass→pass | 22,543 | 24,162 | +7% | 1 | 1 | 0% | 4,594 | 6,087 | +32% | 0 | 0 | — |
case-05 | pass→pass | 31,698 | 29,782 | -6% | 1 | 1 | 0% | 5,679 | 7,195 | +27% | 0 | 0 | — |
case-06 | pass→pass | 15,544 | 29,841 | +92% | 1 | 1 | 0% | 2,936 | 5,842 | +99% | 0 | 0 | — |
case-12 | fail→fail | 12,600 | 6,544 | -48% | 1 | 1 | 0% | 2,124 | 2,070 | -3% | 0 | 0 | — |
case-07 | fail→fail | 11,424 | 7,269 | -36% | 1 | 1 | 0% | 1,898 | 2,182 | +15% | 0 | 0 | — |
case-08 | fail→fail | 12,258 | 7,294 | -40% | 1 | 1 | 0% | 1,977 | 2,208 | +12% | 0 | 0 | — |
case-09 | fail→fail | 12,816 | 9,001 | -30% | 1 | 1 | 0% | 2,070 | 2,324 | +12% | 0 | 0 | — |
case-10 | fail→fail | 16,046 | 18,713 | +17% | 1 | 1 | 0% | 2,553 | 4,196 | +64% | 0 | 0 | — |
case-11 | fail→fail | 16,726 | 7,152 | -57% | 1 | 1 | 0% | 2,627 | 2,114 | -20% | 0 | 0 | — |
case-13 | pass→pass | 8,754 | 5,340 | -39% | 1 | 1 | 0% | 1,435 | 2,560 | +78% | 0 | 0 | — |
case-14 | pass→fail | 13,081 | 7,405 | -43% | 1 | 1 | 0% | 2,023 | 2,206 | +9% | 0 | 0 | — |
case-15 | fail→fail | 9,265 | 1,574 | -83% | 1 | 1 | 0% | 1,501 | 1,886 | +26% | 0 | 0 | — |
case-16 | pass→fail | 12,880 | 9,386 | -27% | 1 | 1 | 0% | 2,139 | 2,367 | +11% | 0 | 0 | — |
case-17 | pass→fail | 11,891 | 7,756 | -35% | 1 | 1 | 0% | 1,866 | 2,317 | +24% | 0 | 0 | — |
case-18 | pass→pass | 16,997 | 8,873 | -48% | 1 | 1 | 0% | 2,842 | 3,172 | +12% | 0 | 0 | — |
case-19 | fail→fail | 18,256 | 10,669 | -42% | 1 | 1 | 0% | 2,953 | 2,406 | -19% | 0 | 0 | — |
case-20 | fail→pass | 11,881 | 11,803 | -1% | 1 | 1 | 0% | 2,186 | 2,982 | +36% | 0 | 0 | — |
case-21 | pass→pass | 13,071 | 8,190 | -37% | 1 | 1 | 0% | 2,207 | 2,983 | +35% | 0 | 0 | — |
case-22 | pass→pass | 6,615 | 2,814 | -57% | 1 | 1 | 0% | 1,263 | 2,113 | +67% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 9 counted toward the lift figure. The other 13 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -9 percentage points is the difference between those two pass rates over the 9 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.