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apidojo-io/apidojo-skills616 installs

analyzing-competitor-twitter-profile-content

Extracts and analyzes tweet history from competitor or brand Twitter profiles using apidojo's Twitter Profile Scraper on Apify. Triggers when the user asks to: get all tweets from a competitor's Twitter account, analyze what a company posts on Twitter, audit a brand's tweet history, track what topics a competitor covers on X, compare Twitter content strategy between brands, extract posts from a company's Twitter timeline, or monitor a competitor's messaging and announcements on Twitter. Returns tweet text, engagement metrics (likes, retweets, replies, views), and author data. Ideal for competitive intelligence teams, PR analysts, and brand strategists.

How do I install this agent skill?

npx skills add https://github.com/apidojo-io/apidojo-skills --skill analyzing-competitor-twitter-profile-content
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill facilitates scraping and analyzing Twitter profile data using the Apify platform. It is functional and generally safe, but carries a low risk of indirect prompt injection due to the processing of external tweet content. It also includes an input parameter for dynamic JavaScript execution in the remote environment, which is a standard feature of the underlying tool but presents a known attack surface.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

What does this agent skill do?

Analyzing Competitor Twitter Profile Content


Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]Twitter profile URLs (x.com or twitter.com formats)
twitterHandlesarrayOptional[]Twitter usernames (without @)
startstringOptional—Tweets after this date (YYYY-MM-DD or YYYY-MM-DD_HH:MM:SS_UTC)
endstringOptional—Tweets before this date (YYYY-MM-DD or YYYY-MM-DD_HH:MM:SS_UTC)
includeNativeRetweetsbooleanOptionalfalseInclude native retweets in results
onlyImagesbooleanOptionalfalseOnly tweets containing images
getRepliesbooleanOptionalfalseInclude tweet replies
minReplyCountnumberOptional—Minimum reply count threshold
getAboutDatabooleanOptionalfalseFetch full profile about data
maxItemsnumberOptionalUnlimitedMaximum tweets to return
customMapFunctionstringOptional—JavaScript function to transform each output object

How to Run

Using run_actor.js (recommended)

# Quick answer (table)
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}'

# Save as CSV
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}' --output results.csv --format csv

# Save as JSON
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}' --output results.json --format json

REST API fallback

curl -X POST "https://api.apify.com/v2/acts/apidojo~twitter-profile-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"twitterHandles": ["competitor_handle"], "maxItems": 100}'

If Apify MCP is available: Use the Apify MCP call_actor tool with actor apidojo~twitter-profile-scraper and the input above.


Scoring & Ranking

Score each tweet for competitive intelligence value:

  • engagement_total = likeCount + retweetCount + replyCount + quoteCount → normalized 0-1 (cap at 10K), weight 0.50
  • viewCount → normalized 0-1 (cap at 500K), weight 0.30
  • has_media (contains image or video) → 0 or 1, weight 0.20
score = 0.50 * min(engagement_total / 10000, 1.0) + 0.30 * min(viewCount / 500000, 1.0) + 0.20 * int(has_media)

Classification

ScoreTierLabel
≥ 0.70AHIGH_IMPACT_TWEET
0.40–0.69BNOTABLE_TWEET
< 0.40CLOW_ENGAGEMENT

Edge Cases

  • Private account: Returns 0 tweets. Check if competitor locked their account.
  • Minimum 40 tweets: First 40 are included at base pricing. For more, cost is $0.0004/tweet.
  • Retweets included: Results include RTs. Filter by checking if text starts with "RT @".
  • Date range + few results: Some accounts tweet rarely — widen date range or remove filter.
  • Multiple competitors: Run for each handle separately and combine datasets.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/apidojo-io/apidojo-skills/analyzing-competitor-twitter-profile-content">View analyzing-competitor-twitter-profile-content on skillZs</a>