Goose-skills twitter-mention-tracker

install

source · Clone the upstream repo

git clone https://github.com/gooseworks-ai/goose-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/gooseworks-ai/goose-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/capabilities/twitter-mention-tracker" ~/.claude/skills/gooseworks-ai-goose-skills-twitter-mention-tracker && rm -rf "$T"

manifest: skills/capabilities/twitter-mention-tracker/SKILL.md

Twitter 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-scraper
```
actor 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