mcpbeat

Apify Trend Analysis

lingxling/apify-trend-analysis

Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.

4k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/lingxling/awesome-skills-cn --skill apify-trend-analysis

The instruction itself

11 sections, as written by the author

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:

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:

  • 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
  • Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

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:

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_TOKEN=your_token

mcpc not found - Ask user to install npm install -g @apify/mcpc

Actor not found - Check Actor ID spelling

Run FAILED - Ask user to check Apify console link in error output

Timeout - Reduce input size or increase --timeout

When to Use

Use this skill when tackling tasks related to its primary domain or functionality as described above.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

How to use it

Copy the folder

Take lingxling/apify-trend-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npm. Without those the skill loads but fails at the first command.