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Agent Orchestration
Skill

/apify-market-research

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

From plugin
sickn33-agentic-awesome-skills-2
46k200 skills
Install
$ npx -y skills add sickn33/agentic-awesome-skills --skill apify-market-research --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/apify-market-research

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

apify-market-research.SKILL.md
name: apify-market-research
description: Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
risk: critical
source: community
date_added: "2026-09-04"

Market Research

Conduct market research using Apify Actors to extract data from multiple platforms.

When to Use

  • You need market sizing, regional demand, pricing, trend, or consumer behavior data.
  • The task is to gather research inputs from maps, travel, Facebook, Instagram, or trend sources with Apify.
  • You need structured market data plus a synthesized view of opportunities or risks.

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 Need | Actor ID | Best 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`

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.
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Repo: sickn33/agentic-awesome-skills