Apify Trend Analysis
Pull cross-platform trend signals from Apify Actors to decide what topics, hashtags, or formats to pursue next.
Overview
apify-trend-analysis is an agent skill most often used in Idea (also Grow) that discovers emerging trends via Apify Actors across Google Trends and major social platforms.
Install
npx skills add https://github.com/apify/agent-skills --skill apify-trend-analysisWhat is this skill?
- Five-step checklist: select Actor, fetch schema via mcpc, confirm user preferences, run script, summarize findings
- Actor routing table for Google Trends plus Instagram-focused scrapers (hashtags, posts, search, API, comments)
- Uses Apify mcpc CLI with APIFY_TOKEN and Node 20.6+ native --env-file support
- Matches user research need (search trends, hashtag metrics, visual posts, engagement comments) to a specific Actor ID
- Outputs structured trend data to inform content strategy decisions
- 5-step workflow checklist
- 8+ Actor routing rows in the trend-type table (Google Trends and Instagram family)
Adoption & trust: 2.7k installs on skills.sh; 2.1k GitHub stars; 1/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need timely trend data scattered across Google Trends and social apps but lack a consistent way to fetch, compare, and summarize it for strategy.
Who is it for?
Solo builders with an Apify token who want agent-guided platform trend pulls before committing to niches, campaigns, or content pillars.
Skip if: Offline-only research, teams without Apify billing/APIFY_TOKEN, or workflows that forbid third-party scraping of social platforms.
When should I use this skill?
Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.
What do I get? / Deliverables
You get a completed five-step trend run with Actor-backed datasets and an agent-written summary you can feed into validation, content planning, or launch messaging.
- Platform trend dataset per chosen Actor
- User-configured export file
- Narrative summary of findings
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Idea/research is where emerging demand and cultural signals are discovered before you commit build or content calendars. Research subphase covers competitor and trend discovery via external data, which this skill automates across Google Trends and social platforms.
Where it fits
Run google-trends-scraper to compare search interest before picking a SaaS niche.
Use hashtag stats Actors to see if a proposed audience segment shows sustained engagement.
Refresh weekly content themes using instagram-search-scraper trending discoveries.
Align launch posts with visual trends surfaced by instagram-post-scraper analysis.
How it compares
Apify Actor workflow skill—not a built-in MCP server; you choose per-platform Actors instead of one generic trends API.
Common Questions / FAQ
Who is apify-trend-analysis for?
Indie founders, content solo operators, and growth-minded builders who already use or can afford Apify and want multi-platform trend extraction without writing scrapers by hand.
When should I use apify-trend-analysis?
During Idea/research to spot niches and hashtags; during Validate/scope to sanity-check demand; during Grow/content when refreshing pillars; during Launch/distribution when timing posts to rising topics.
Is apify-trend-analysis safe to install?
It requires APIFY_TOKEN, shell, and network access to run Actors; review the Security Audits panel on this page and Apify/platform ToS before scraping production accounts.
SKILL.md
READMESKILL.md - Apify Trend Analysis
# Trend Analysis Discover and track emerging trends using Apify Actors to extract data from multiple platforms. ## Prerequisites (No need to check it upfront) - `.env` file with `APIFY_TOKEN` - Node.js 20.6+ (for native `--env-file` support) - `mcpc` CLI tool: `npm install -g @apify/mcpc` ## Workflow Copy this checklist and track progress: ``` Task Progress: - [ ] Step 1: Identify trend type (select Actor) - [ ] Step 2: Fetch Actor schema via mcpc - [ ] Step 3: Ask user preferences (format, filename) - [ ] Step 4: Run the analysis script - [ ] Step 5: Summarize findings ``` ### Step 1: Identify Trend Type Select the appropriate Actor based on research needs: | User Need | Actor ID | Best For | |-----------|----------|----------| | Search trends | `apify/google-trends-scraper` | Google Trends data | | Hashtag tracking | `apify/instagram-hashtag-scraper` | Hashtag content | | Hashtag metrics | `apify/instagram-hashtag-stats` | Performance stats | | Visual trends | `apify/instagram-post-scraper` | Post analysis | | Trending discovery | `apify/instagram-search-scraper` | Search trends | | Comprehensive tracking | `apify/instagram-scraper` | Full data | | API-based trends | `apify/instagram-api-scraper` | API access | | Engagement trends | `apify/export-instagram-comments-posts` | Comment tracking | | Product trends | `apify/facebook-marketplace-scraper` | Marketplace data | | Visual analysis | `apify/facebook-photos-scraper` | Photo trends | | Community trends | `apify/facebook-groups-scraper` | Group monitoring | | YouTube Shorts | `streamers/youtube-shorts-scraper` | Short-form trends | | YouTube hashtags | `streamers/youtube-video-scraper-by-hashtag` | Hashtag videos | | TikTok hashtags | `clockworks/tiktok-hashtag-scraper` | Hashtag content | | Trending sounds | `clockworks/tiktok-sound-scraper` | Audio trends | | TikTok ads | `clockworks/tiktok-ads-scraper` | Ad trends | | Discover page | `clockworks/tiktok-discover-scraper` | Discover trends | | Explore trends | `clockworks/tiktok-explore-scraper` | Explore content | | Trending content | `clockworks/tiktok-trends-scraper` | Viral content | ### Step 2: Fetch Actor Schema Fetch the Actor's input schema and details dynamically using mcpc: ```bash export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content" ``` Replace `ACTOR_ID` with the selected Actor (e.g., `apify/google-trends-scraper`). This returns: - Actor description and README - Required and optional input parameters - Output fields (if available) ### Step 3: Ask User Preferences Before running, ask: 1. **Output format**: - **Quick answer** - Display top few results in chat (no file saved) - **CSV** - Full export with all fields - **JSON** - Full export in JSON format 2. **Number of results**: Based on character of use case ### Step 4: Run the Script **Quick answer (display in chat, no file):** ```bash node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ --actor "ACTOR_ID" \ --input 'JSON_INPUT' ``` **CSV:** ```bash node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ --actor "ACTOR_ID" \ --input 'JSON_INPUT' \ --output YYYY-MM-DD_OUTPUT_FILE.csv \ --format csv ``` **JSON:** ```bash node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ --actor "ACTOR_ID" \ --input 'JSON_INPUT' \ --output YYYY-MM-DD_OUTPUT_FILE.json \ --format json ``` ### Step 5: Summarize Findings After completion, report: - Number of results found - File location and name - Key trend insights - Suggested next steps (deeper analysis, content opportunities) ## Error Handling `APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKE