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 scraping-twitter-profilesAvant 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.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
Scraping Twitter Profiles
Bulk profile data export for any set of Twitter/X usernames. Returns account-level metadata: follower counts, bios, join dates, verification status.
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: Normalize username list
- [ ] Step 2: Run twitter-user-scraper
- [ ] Step 3: Poll for SUCCEEDED
- [ ] Step 4: Deliver profile datasetStep 1: Normalize
Remove @ symbols, deduplicate, validate no empty strings.
Step 2: Run the Actor
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 jsonAPIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input:
{
"usernames": ["handle1", "handle2", "handle3"]
}REST API fallback:
bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"usernames": ["handle1", "handle2"]}'Save id as RUN_ID. Poll until status = SUCCEEDED:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID?token=$APIFY_TOKEN" | grep '"status"'Fetch results:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN&format=json"Step 3: Handle Edge Cases
- Missing accounts in results: Account suspended, deleted, or handle changed. Note missing handles in output.
- Private accounts: Returns profile metadata but no tweet content — flag
isPrivate: truerows. - Deactivated accounts: Returns null or empty object — exclude from final dataset.
Output Format
# Twitter Profile Dataset
Accounts requested: N | Accounts returned: N | Missing: N
| Username | Display Name | Followers | Following | Tweets | Verified | Bio (truncated) | Joined |
|----------|-------------|-----------|-----------|--------|----------|-----------------|--------|
| ... | ... | ... | ... | ... | ... | ... | ... |
Available fields: username, displayName, followersCount, followingCount, tweetCount,
isVerified, isBlueVerified, description, location, url, profileImageUrl, createdAt, isPrivateTroubleshooting
Some handles missing from results: Accounts may be suspended or renamed — cross-reference manually. Large lists (> 1000): Break into batches of 500 and run sequentially.
