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finding-freelancers-by-skill-on-twitter

finding-freelancers-by-skill-on-twitter

github.com/apidojo-ioOther1757 installsUpdated 24w ago
Repository

About finding-freelancers-by-skill-on-twitter

A skill for finding freelancers and independent contractors on Twitter through skill-related posts, profile signals, and availability indicators. It collects candidate handles, enriches profiles, and scores fit for recruiting workflows.

Key features

  1. 01Search skill and hiring-related tweets
  2. 02Collect unique profile handles
  3. 03Enrich candidates with profile data
  4. 04Score skills, availability, and activity

Use cases

  1. 01Build a shortlist for a freelance role
  2. 02Find profiles signaling openness to projects

MCP support

Optionally uses the Apify MCP server to run tweet and Twitter user scraper actors.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-freelancers-by-skill-on-twitter

After installing, type/finding-freelancers-by-skill-on-twitterin Claude Code to confirm it loaded.

Details

From the project README

Finding Freelancers And Independent Contractors on Twitter

Discovers freelancers and independent contractors 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

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]Twitter profile or tweet URLs
twitterHandlesarrayOptional[]Twitter usernames (without @)
twitterUserIdsarrayOptional[]Twitter user IDs
getFollowersbooleanOptionalfalseExtract follower lists
getFollowingbooleanOptionalfalseExtract following lists
getRetweetersbooleanOptionalfalseExtract retweeters of a tweet URL
includeUnavailableUsersbooleanOptionalfalseInclude unavailable/suspended users
maxItemsnumberOptionalUnlimitedMaximum users to return
customMapFunctionstringOptional—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):

# 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": ["freelance [SKILL]", "[SKILL] for hire", "available for contract [SKILL]"],
  "maxItems": 300,
  "tweetLanguage": "en"
}

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": ["freelance [SKILL]", "[SKILL] for hire", "available for contract [SKILL]"], "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:

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"usernames": ["handle1", "handle2"]}'
Step 3: Filter and Score

Skill confirmation: bio contains keywords: "freelance", "independent", "for hire", "consulting", "contract", "available", "hire me", "DM for work"

availability_signal = bio or recent tweets contain 'available', 'taking clients', 'open for projects', 'DM for rates'

Candidate score:

candidate_score = (skill_confirmed ? 1 : 0) * 0.35
                + (open_to_work_signal ? 1 : 0) * 0.30
                + (followerCount in 200..20000 ? 1 : 0.6) * 0.20
                + (tweeted_in_last_30_days ? 1 : 0) * 0.15

Activity: active (< 30 days) | passive (30–90 days) | dormant (> 90 days)

Step 4: Edge Cases
  • Company/brand accounts in results: Filter where followerCount > 50K AND bio contains no personal pronouns; these are likely brand accounts
  • < 20 candidates found: Broaden skill term; remove location or seniority filter; try adjacent skills
  • Bot detection: Flag followerCount / followingCount < 0.05 AND tweetsCount < 20 as potential bot
  • Location not matching: Bio location is free text — use fuzzy match; accept partial city/country names

Output Format

# Freelancers And Independent Contractors Candidates: [FREELANCE_SKILL]
Profiles found: [N] | Open-to-work: [N] | Active: [N] | Date: [DATE]

## Priority: Open-to-Work Candidates
| Name | @Handle | Specialty | Location | Followers | Last Active | Score |
|------|---------|----------|---------|-----------|------------|-------|

## Passive Candidates
| Name | @Handle | Specialty | Location | Followers | Score |
|------|---------|----------|---------|-----------|-------|

## Bio Highlights (Top 5)
1. @[handle]: "[bio excerpt]"

Troubleshooting

All results are agencies/companies not individuals: Add personal pronouns filter or search "I am a [role]", "I do [skill]". Role too generic returns too many results: Add location OR seniority qualifier. No open-to-work signals: Most candidates don't signal publicly — treat passive candidates as warm leads with personalized outreach referencing their recent content.

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