Skill detail
finding-startup-employees-for-recruiting
Finds professionals currently employed at startups to recruit using Apify Twitter scrapers, returning handle, name, company, role level, and career-change signals.
Why we recommend it: Directly supports recruiting by sourcing startup employees as candidates via Twitter scraping.
Inspect before use
Read the source instructions and check the requirements before you install this skill.
SKILL.md
The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.
---
name: finding-startup-employees-for-recruiting
description: >
Finds professionals currently employed at startups to recruit using apidojo's Twitter scrapers on Apify.
Triggers when the user asks to: find startup employees to recruit on Twitter, discover people working at early-stage startups for talent poaching, find employees at Series A or B companies on X who might be open to new roles, identify talent at competitor startups via Twitter, build a talent map of startup employees in a sector on Twitter, find people with startup experience for recruiting, or discover potential candidates at named startup companies.
Returns handle, name, current company (from bio), role level, follower count, and career change signals.
Ideal for technical recruiters, startup talent leads, and VC-backed company HR teams.
license: Apache-2.0
metadata:
author: apidojo
version: "1.0"
apify-actors: apidojo/twitter-user-scraper, apidojo/tweet-scraper
---
# Finding Professionals Currently Employed At Startups on Twitter
Discovers professionals currently employed at startups on Twitter via skill keywords, portfolio/project signals, and open-to-work indicators. Twitter surfaces professionals who actively discuss their craft — a strong passive candidate signal.
## Prerequisites
- `APIFY_TOKEN` environment variable set
- Optional: Apify MCP server installed
## Inputs
| Parameter | Type | Required | Default | Notes |
|-----------|------|----------|---------|-------|
| `startUrls` | array | Optional | `[]` | Twitter profile or tweet URLs |
| `twitterHandles` | array | Optional | `[]` | Twitter usernames (without @) |
| `twitterUserIds` | array | Optional | `[]` | Twitter user IDs |
| `getFollowers` | boolean | Optional | `false` | Extract follower lists |
| `getFollowing` | boolean | Optional | `false` | Extract following lists |
| `getRetweeters` | boolean | Optional | `false` | Extract retweeters of a tweet URL |
| `includeUnavailableUsers` | boolean | Optional | `false` | Include unavailable/suspended users |
| `maxItems` | number | Optional | Unlimited | Maximum users to return |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |
## Workflow
```
Progress:
- [ ] Step 1: Search for role-specific tweets
- [ ] Step 2: Collect unique handles
- [ ] Step 3: Enrich profiles
- [ ] Step 4: Score candidate fit
- [ ] Step 5: Deliver candidate list
```
### Step 1: Search Queries
**Recommended — run_actor.js (handles waiting, output, and file saving automatically):**
```bash
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~twitter-user-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~twitter-user-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~twitter-user-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": ["at [COMPANY]", "engineer at [STARTUP]", "working at [SECTOR] startup"],
"maxItems": 300,
"tweetLanguage": "en"
}
```
**REST API fallback:**
```bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": ["at [COMPANY]", "engineer at [STARTUP]", "working at [SECTOR] startup"], "maxItems": 300}'
```
Collect unique `author.username` from results.
### Step 2: Enrich Profiles
**If Apify MCP is available:**
```
Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input: {"usernames": ["[username1]", "[username2]", "..."]}
```
**REST API fallback:**
```bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Read the full source on GitHub (opens external page)