monitoring-twitter-for-competitor-job-posts

v2026.09.24

Monitors Twitter for competitor hiring announcements to track growth signals using apidojo's Tweet scraper. Triggers when the user asks to: monitor competitor job postings on Twitter, track hiring signals from competitor companies on X, find out what roles competitors are hiring for on Twitter, analyze competitor team growth from their Twitter activity, monitor startup hiring signals for competitive intelligence, track which departments competitors are growing via their Twitter, or discover competitor expansion strategies from job post tweets. Returns company handle, role being posted, department, posting date, urgency signals, and growth pattern. Ideal for competitive intelligence teams, recruiters targeting competitor employees, and investors tracking company growth.

GitHub
Install command
npx skhub add apidojo-io/monitoring-twitter-for-competitor-job-posts
Markdown
SKILL.md

Monitoring Twitter For Competitor Job Posts

Executes monitoring twitter for competitor job posts using apidojo scrapers. Part of the apidojo intelligence skills library.

Prerequisites

  • APIFY_TOKEN environment variable set
  • Optional: Apify MCP server installed

Inputs

ParameterTypeRequiredDefaultNotes
searchTermsarray✅[]Twitter advanced search queries (e.g. ["#AI lang:en", "from:NASA"])
sortstringOptionalTopSort order: Latest, Top, or Latest+Top
tweetLanguagestringOptional—ISO 639-1 language code (e.g. en)
maxItemsnumberOptionalUnlimitedMaximum tweets to return
onlyVerifiedUsersbooleanOptionalfalseOnly tweets from verified users
onlyTwitterBluebooleanOptionalfalseOnly Twitter Blue subscribers
onlyImagebooleanOptionalfalseOnly tweets with images
onlyVideobooleanOptionalfalseOnly tweets with videos
onlyQuotebooleanOptionalfalseOnly quote tweets
authorstringOptional—Filter to a specific author handle
inReplyTostringOptional—Tweets replying to a specific handle
mentioningstringOptional—Tweets mentioning a specific handle
geotaggedNearstringOptional—Tweets near a location
withinRadiusstringOptional—Radius around geotaggedNear
geocodestringOptional—Lat/lng + radius string
placeObjectIdstringOptional—Tweets tagged with a place
minimumRetweetsnumberOptional—Minimum retweet count
minimumFavoritesnumberOptional—Minimum like count
minimumRepliesnumberOptional—Minimum reply count
startstringOptional—Tweets after this date (YYYY-MM-DD)
endstringOptional—Tweets before this date (YYYY-MM-DD)
includeSearchTermsbooleanOptionalfalseAdd the matched search term to each tweet
customMapFunctionstringOptional—JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run tweet-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output

Step 2: Run the Actor

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tweet-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~tweet-scraper"
Input:
{
  "searchTerms": ["[COMPETITOR] hiring", "[COMPETITOR] join our team", "[COMPETITOR] job opening"],
  "maxItems": 100
}

REST API fallback:

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["[COMPETITOR] hiring", "[COMPETITOR] join our team", "[COMPETITOR] job opening"], "maxItems": 100}'

Wait for SUCCEEDED. Fetch dataset:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

Step 3: Classify Results

classification: AGGRESSIVE_GROWTH (> 5 roles/month) | STEADY_GROWTH (2-5 roles/month) | OPPORTUNISTIC (1-2 roles) | REPLACEMENT_ONLY (role title identical to recent departure signal)

Step 4: Score Each Result

score = growth_signal_score = (roles_posted_in_30_days / 5, max 1) * 0.50 + (engineering_role ? 1.2 : 1) * department_weight * 0.30 + (urgency_language ? 1 : 0.5) * 0.20

Step 5: Edge Cases

  • Competitor may post jobs across many channels but only announce key roles on Twitter — Twitter hiring posts often signal strategic priorities, not routine backfills

Additional fallbacks:

  • < 20 results: Broaden search terms; remove secondary filters
  • No results: Verify the search terms are correct; try alternate phrasings
  • Data quality issues: Remove entries with missing key fields; note count in output

Output Format

# Monitoring Twitter For Competitor Job Posts
Results: [N] | Date: [DATE]

| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |

## Summary
Top result: [description]
Key finding: [insight]

Troubleshooting

Too few results: Broaden the primary search term; remove restrictive filters. Low quality results: Apply minimum score threshold (≥ 0.50) to filter noise. Actor fails to run: Verify API key; check actor status at apify.com/apidojo.

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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Apache-2.0

Source path

skills/intent/monitoring-twitter-for-competitor-job-posts

Default branch

main

Latest commit

ffbdc00

Tree SHA

c7df562