Twitter Mention Tracker Agent Skill
> Search and scrape Twitter/X posts using Apify. Use when you need to find tweets, track brand mentions, monitor competitors on Twitter, or analyze Twitter discussions.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/gooseworks-ai/goose-skills --skill twitter-mention-trackerWhat comes with it
8 402 bytes besides the instructionThe instruction itself
10 sections, as written by the authorTwitter Mention Tracker
Search Twitter/X posts using the Apify apidojo/tweet-scraper actor.
Quick Start
Requires APIFY_API_TOKEN env var (or --token flag).
# Search with date range (recommended -- uses Twitter native since:/until: operators)
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
--query "YourCompany" --since 2026-02-15 --until 2026-02-23
# Quick summary of recent mentions
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
--query "@yourhandle" --max-tweets 20 --output summary
# Search without date filtering
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
--query "AI content marketing" --max-tweets 50
Date Filtering
Important: The apidojo/tweet-scraper actor's built-in date parameters are unreliable.
This script embeds since:YYYY-MM-DD and until:YYYY-MM-DD directly into the search query
string, using Twitter's native advanced search syntax. This ensures date filtering works
correctly server-side.
How the Script Works
- Builds a search term with the query quoted and date operators appended
- Calls the Apify
apidojo/tweet-scraperactor via REST API - Polls until the run completes, then fetches the dataset
- Deduplicates by tweet ID/URL
- Applies optional keyword filtering (client-side)
- Sorts by likes (descending) and outputs JSON or summary
CLI Reference
| Flag | Default | Description |
|------|---------|-------------|
| --query | *required* | Search query (quoted in Twitter search) |
| --since | none | Start date YYYY-MM-DD (inclusive) |
| --until | none | End date YYYY-MM-DD (exclusive) |
| --max-tweets | 50 | Max tweets to scrape |
| --keywords | none | Additional filter keywords (comma-separated, OR logic) |
| --output | json | Output format: json or summary |
| --token | env var | Apify token (prefer APIFY_API_TOKEN env var) |
| --timeout | 300 | Max seconds to wait for the Apify run |
Direct API Usage
{
"searchTerms": ["\"YourCompany\" since:2026-02-15 until:2026-02-22"],
"maxTweets": 50,
"searchMode": "live"
}
Output Format
Tweets are returned as JSON array sorted by likes. Each tweet has:
{
"id": "...",
"text": "Tweet text...",
"fullText": "Full tweet text...",
"likeCount": 42,
"retweetCount": 5,
"replyCount": 3,
"viewCount": 1200,
"createdAt": "2026-02-18T12:00:00.000Z",
"author": {"userName": "handle", "name": "Display Name", ...},
"twitterUrl": "https://twitter.com/..."
}
Common Workflows
Competitor Monitoring
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
--query "CompetitorName" --since 2026-02-15 --until 2026-02-23 --output summary
Brand Mention Tracking
python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
--query "@YourHandle OR \"YourBrand\"" --max-tweets 100
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How to use it
Take gooseworks-ai/twitter-mention-tracker from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.