Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-designers-and-creatives-on-twitterAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
Finding Designers And Creative Professionals on Twitter
Discovers designers and creative professionals 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_TOKENenvironment 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 listStep 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 jsonAPIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~tweet-scraper"
Input:
{
"searchTerms": ["UX designer", "product designer", "portfolio", "[DISCIPLINE] open to work"],
"maxItems": 300,
"tweetLanguage": "en"
}REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": ["UX designer", "product designer", "portfolio", "[DISCIPLINE] open to work"], "maxItems": 300}'Collect unique author.username from results.
Step 2: Enrich Profiles
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input: {"usernames": ["[username1]", "[username2]", "..."]}REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"usernames": ["handle1", "handle2"]}'Step 3: Filter and Score
Skill confirmation: bio contains keywords: "UX", "UI", "product design", "graphic design", "motion", "brand design", "Figma", "Sketch", "Adobe"
portfolio_link_signal = bio contains figma.com, behance.net, dribbble.com, or personal domain → strong talent signal
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) * 0.15Activity: active (< 30 days) | passive (30–90 days) | dormant (> 90 days)
Step 4: Edge Cases
- Company/brand accounts in results: Filter where
followerCount > 50KAND 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 < 0.05ANDtweetsCount < 20as potential bot - Location not matching: Bio location is free text — use fuzzy match; accept partial city/country names
Output Format
# Designers And Creative Professionals Candidates: [DESIGN_DISCIPLINE]
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.
