Imported from apidojo-io/apidojo-skills (skills/intent/tracking-hiring-signals-from-company-tweets/SKILL.md). Install upstream with npx skills add apidojo-io/apidojo-skills --skill tracking-hiring-signals-from-company-tweets. Copyright stays with the author (Apache-2.0).

Tracking Hiring Signals from Company Tweets

Monitors company Twitter accounts for hiring announcements and growth signals. Companies tweet about openings before jobs.page or LinkedIn posts go live — Twitter is an early signal channel.

Prerequisites

APIFY_TOKEN environment variable set
Optional: Apify MCP server installed

Inputs

Parameter	Type	Required	Default	Notes
`searchTerms`	array	✅	`[]`	Twitter advanced search queries (e.g. `["#AI lang:en", "from:NASA"]`)
`sort`	string	Optional	`Top`	Sort order: `Latest`, `Top`, or `Latest+Top`
`tweetLanguage`	string	Optional	—	ISO 639-1 language code (e.g. `en`)
`maxItems`	number	Optional	Unlimited	Maximum tweets to return
`onlyVerifiedUsers`	boolean	Optional	`false`	Only tweets from verified users
`onlyTwitterBlue`	boolean	Optional	`false`	Only Twitter Blue subscribers
`onlyImage`	boolean	Optional	`false`	Only tweets with images
`onlyVideo`	boolean	Optional	`false`	Only tweets with videos
`onlyQuote`	boolean	Optional	`false`	Only quote tweets
`author`	string	Optional	—	Filter to a specific author handle
`inReplyTo`	string	Optional	—	Tweets replying to a specific handle
`mentioning`	string	Optional	—	Tweets mentioning a specific handle
`geotaggedNear`	string	Optional	—	Tweets near a location
`withinRadius`	string	Optional	—	Radius around geotaggedNear
`geocode`	string	Optional	—	Lat/lng + radius string
`placeObjectId`	string	Optional	—	Tweets tagged with a place
`minimumRetweets`	number	Optional	—	Minimum retweet count
`minimumFavorites`	number	Optional	—	Minimum like count
`minimumReplies`	number	Optional	—	Minimum reply count
`start`	string	Optional	—	Tweets after this date (YYYY-MM-DD)
`end`	string	Optional	—	Tweets before this date (YYYY-MM-DD)
`includeSearchTerms`	boolean	Optional	`false`	Add the matched search term to each tweet
`customMapFunction`	string	Optional	—	JavaScript function to transform each output object

Workflow

Progress:
- [ ] Step 1: Search for hiring-signal tweets in sector
- [ ] Step 2: (Optional) Scrape specific company accounts
- [ ] Step 3: Extract role and team info from tweet text
- [ ] Step 4: Score growth signal strength
- [ ] Step 5: Deliver hiring intelligence report

Step 1: Search Hiring Signals

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": ["we're hiring [SECTOR]", "join our team [SECTOR]", "[ROLE] hiring [SECTOR]"],
  "maxItems": 300
}

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": ["we are hiring fintech", "join our team SaaS startup", "software engineer hiring"],
    "maxItems": 300
  }'

Step 2: Extract Role Signals from Tweet Text

role_mentioned = extract noun phrases after "hiring a/an", "looking for a/an", "seeking a"
team_mentioned = extract from: "engineering team", "sales team", "marketing", "product team"
urgency = "immediately", "ASAP", "urgent" → HIGH; "growing team" → MEDIUM; general → LOW

Step 3: Growth Signal Score

hiring_signal_score = (is_confirmed_company_account ? 1 : 0.5) * 0.30
                    + (role_is_specific ? 1 : 0.5) * 0.25
                    + (post_is_recent: ≤7 days = 1, 8-14 = 0.7, 15-30 = 0.4) * 0.25
                    + (link_to_job_page ? 1 : 0) * 0.20

Growth tier: Multiple hiring tweets in 30 days = HIGH_GROWTH; 1-2 = STEADY_HIRE; no link = SIGNAL_ONLY

Step 4: Edge Cases

Retweets from employee accounts: If a company employee retweets a job post, keep — it's still a valid signal; note it's not the company's official account
Job boards posting on behalf of company: Filter out accounts named "JobsAt[Company]", staffing agencies, or accounts posting > 10 hiring tweets/day (aggregators)
Role extraction fails: Note the tweet verbatim and mark role = "unspecified" — still a growth signal
Same company posts 5 roles: Deduplicate by author.username; count unique companies, not unique tweets

Output Format

# Hiring Signal Intelligence: [SECTOR/ROLE]
Tweets analyzed: [N] | Companies with hiring signals: [N] | Date: [DATE]

## High-Growth Companies (Multiple Roles Posted)
| Company | @Handle | Roles Mentioned | Teams | Posts | Link to Jobs | Score |
|---------|---------|----------------|-------|-------|-------------|-------|
| [name] | @[handle] | [role list] | [eng/mktg] | [N] | [Yes/No] | [0.XX] |

## Single Hire Signals
| Company | @Handle | Role | Team | Tweet Date | Job Link |
|---------|---------|------|------|-----------|---------|

## Role Distribution Across All Companies
| Role Category | # Companies Hiring | Urgency |
|--------------|-------------------|---------|
| Engineering | [N] | [High/Med] |
| Marketing | [N] | |
| Sales | [N] | |

Troubleshooting

Results dominated by job boards: Add negative terms to search: -jobs -jobboard -staffing -recruiting Sector too broad: Narrow with a sub-sector or specific stage: "Series A fintech" instead of "fintech". Job links are broken/expired: Hiring tweets are posted in real-time; check within 48h for best link validity.

tracking-hiring-signals-from-company-tweets

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