Awesome-omni-skill apify-market-research

Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.

install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/backend/apify-market-research" ~/.claude/skills/diegosouzapw-awesome-omni-skill-apify-market-research && rm -rf "$T"
manifest: skills/backend/apify-market-research/SKILL.md
safety · automated scan (medium risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
  • global npm install
  • dumps environment variables
  • references .env files
Always read a skill's source content before installing. Patterns alone don't mean the skill is malicious — but they warrant attention.
source content

Market Research

Conduct market research 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 market research 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 Market Research Type

Select the appropriate Actor based on research needs:

User NeedActor IDBest For
Market density
compass/crawler-google-places
Location analysis
Geospatial analysis
compass/google-maps-extractor
Business mapping
Regional interest
apify/google-trends-scraper
Trend data
Pricing and demand
apify/facebook-marketplace-scraper
Market pricing
Event market
apify/facebook-events-scraper
Event analysis
Consumer needs
apify/facebook-groups-scraper
Group research
Market landscape
apify/facebook-pages-scraper
Business pages
Business density
apify/facebook-page-contact-information
Contact data
Cultural insights
apify/facebook-photos-scraper
Visual research
Niche targeting
apify/instagram-hashtag-scraper
Hashtag research
Hashtag stats
apify/instagram-hashtag-stats
Market sizing
Market activity
apify/instagram-reel-scraper
Activity analysis
Market intelligence
apify/instagram-scraper
Full data
Product launch research
apify/instagram-api-scraper
API access
Hospitality market
voyager/booking-scraper
Hotel data
Tourism insights
maxcopell/tripadvisor-reviews
Review analysis

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.,
compass/crawler-google-places
).

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):

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 market insights
  • Suggested next steps (deeper analysis, validation)

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