apidojo-io/apidojo-skills

analyzing-competitor-twitter-profile-content

Extracts and analyzes tweet history from competitor or brand Twitter profiles using apidojo's Twitter Profile Scraper on Apify.

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使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/apidojo-io/apidojo-skills --skill analyzing-competitor-twitter-profile-content

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
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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-DDHH:MM:SSUTC)
endstringOptional—Tweets before this date (YYYY-MM-DD or YYYY-MM-DDHH:MM:SSUTC)
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)

bash
# 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

bash
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
python
score = 0.50 * min(engagement_total / 10000, 1.0) + 0.30 * min(viewCount / 500000, 1.0) + 0.20 * int(has_media)

Classification

ScoreTierLabel
≥ 0.70AHIGHIMPACTTWEET
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.

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