Skillshub apify-competitor-intelligence
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/apify/agent-skills/apify-competitor-intelligence" ~/.claude/skills/comeonoliver-skillshub-apify-competitor-intelligence && rm -rf "$T"
manifest:
skills/apify/agent-skills/apify-competitor-intelligence/SKILL.mdsource content
Competitor Intelligence
Analyze competitors using Apify Actors to extract data from multiple platforms.
Prerequisites
(No need to check it upfront)
file with.envAPIFY_TOKEN- Node.js 20.6+ (for native
support)--env-file
CLI tool:mcpcnpm install -g @apify/mcpc
Workflow
Copy this checklist and track progress:
Task Progress: - [ ] Step 1: Identify competitor analysis 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 Competitor Analysis Type
Select the appropriate Actor based on analysis needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Competitor business data | | Location analysis |
| Competitor contact discovery | | Email extraction |
| Feature benchmarking | | Detailed business data |
| Competitor review analysis | | Review comparison |
| Hotel competitor data | | Hotel benchmarking |
| Hotel review comparison | | Review analysis |
| Competitor ad strategies | | Ad creative analysis |
| Competitor page metrics | | Page performance |
| Competitor content analysis | | Post strategies |
| Competitor reels performance | | Reels analysis |
| Competitor audience analysis | | Comment sentiment |
| Competitor event monitoring | | Event tracking |
| Competitor audience overlap | | Follower analysis |
| Competitor review benchmarking | | Review comparison |
| Competitor ad monitoring | | Ad discovery |
| Competitor profile metrics | | Profile analysis |
| Competitor content monitoring | | Post tracking |
| Competitor engagement analysis | | Comment analysis |
| Competitor reel performance | | Reel metrics |
| Competitor growth tracking | | Follower tracking |
| Comprehensive competitor data | | Full analysis |
| API-based competitor analysis | | API access |
| Competitor video analysis | | Video metrics |
| Competitor sentiment analysis | | Comment sentiment |
| Competitor channel metrics | | Channel analysis |
| TikTok competitor analysis | | TikTok data |
| Competitor video strategies | | Video analysis |
| Competitor TikTok profiles | | Profile data |
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:
- 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 competitors analyzed
- File location and name
- Key competitive insights
- Suggested next steps (deeper analysis, benchmarking)
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