Trend Scanner
Give it a topic and it searches Reddit, X, and YouTube from the last 30 days in parallel, scores what it finds, and synthesizes a single briefing on what people are actually reacting to — not what ranks in search.
Before & after
Same prompt, same agent — the only difference is the skill.
You could search Google, Reddit, and Twitter to see what people are talking about and discussing. You'd look for recent posts and discussions across different platforms. Sorting by date helps find the latest trends in the community. You might check a few key subreddits or accounts that cover AI topics specifically. Looking at engagement metrics like likes and shares can tell you what's actually resonating with audiences. You could summarize what you find into a briefing. It takes some manual searching and reading across multiple sources. Would you like me to suggest some specific places to look, or help you synthesize what you find into meaningful insights? Manual research can be time-consuming.
TREND BRIEFING - AI AGENTS (July 2026, Last 30 days) DATA SOURCES: Parallel search across Reddit, X (Twitter), YouTube Recency window: June 31 - July 31, 2026 Engagement scoring: Comment count + share volume + upvote ratio TOP TREND 1: "AI Agents in Production" (engagement score: 8.7/10) Where it's winning: r/openai (r/Claude), HackerNews, X accounts @AnthropicAI, @karpathy What devs say: "Finally shipping Claude agents to production. Worked through 48-hour context windows, saved us 200k on labor." Why it matters: Production deployment signals = maturity proof Sources cited: 47 Reddit posts, 312 X mentions, 8 YouTube videos (Loom recordings) Representative quote: "Context window fixed our agentic loop problem. Agents stay in character across 12-hour sessions now." TOP TREND 2: "Prompt Injection Fears (Overstated?)" (engagement score: 7.2/10) Where: r/MachineLearning, r/programming, security-focused X threads What devs say: "Turns out well-prompt-engineered agents are actually robust. Went 2 months in prod, zero injection exploits." Why it matters: Production confidence up 35% month-over-month Counter-narrative detected: "But your users are well-behaved. Try this at enterprise scale." Contention level: Medium (useful debate, not settled) TOP TREND 3: "Agent Reliability Metrics" (engagement score: 6.8/10) Where: r/programming, YouTube dev channels (GitHub Actions tutorials) What devs say: "Built a dashboard for agent hallucination rates, false positive capture, latency. It's the boring infrastructure we actually need." Why it matters: Shift from novelty to operational maturity Emerging tools: PostHog dashboards for agent tracing, custom observability CONSENSUS FINDING: Agents are moving from research/demo phase to production operations phase. Community focus: reliability, not capability. Contrary opinion: 23% of discussion emphasizes "agents are still overstated for most use cases." Valid context: mostly small-team builders, not enterprise. RECOMMENDATION: Agents are stable for production, contingent on robust prompt engineering + observability. Monitor reliability concerns in Q3.
About this skill
name: trend-scanner description: Use when Give it a topic and it searches Reddit, X, and YouTube from the last 30 days in parallel, scores what it finds, and synthesizes a single briefing on what people are actually reacting to — not what ranks in search.
Trend Scanner
Built to answer "where do you find out about new skills and trends?" Feed it a topic (the demo uses "Claude Fable") and it first figures out which subreddits, X accounts, and YouTube channels are relevant, then searches all of them in parallel across the last 30 days. Results are scored and synthesized into one briefing showing what the community is actually engaging with and reacting to, rather than whatever ranks highest in a generic Google search. The creator notes it uses cookies for some of its search sources, so there are security considerations worth checking before use.
What you get
- Parallel search across Reddit, X, and YouTube for a given topic, 30-day recency window, engagement-scored synthesis instead of generic search-rank results, single consolidated briefing output with sources cited.
Customize your output
- Adjust the recency window and which platforms to include or exclude from the parallel search.
Example output
Query: "Claude Fable" — briefing surfaced what the community had been discussing over the past month across Reddit, X, and YouTube, cited with sources, instead of generic top search results.
Best for
Anyone tracking fast-moving AI/tech trends who wants real community reaction instead of SEO-optimized search results.
SKILL.md preview
---
name: trend-scanner
description: Use this skill when a creator wants to know what's actually trending and being reacted to around a topic, pulled from Reddit, X, and YouTube rather than generic search rankings.
version: 1.0.0
category: Research / Content Discovery
author: AgentVolt
license: proprietary
tags:
- research
- content-discovery
- standard
---
# Trend Scanner
Given a topic, identifies the relevant subreddits, X accounts, and YouTube channels, searches all of them in parallel across the last 30 days, and synthesizes one briefing on what the community is actually reacting to.
## When to use
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