building-full-social-audit-for-brand

该 Skill 面向品牌在 Twitter、Instagram、TikTok、YouTube 的社交表现，调用 Apify 抓取器获取粉丝数、互动率、内容结构与发帖频率，并按平台权重计算品牌健康分，输出审计表格和发现；依赖 APIFY_TOKEN，且引用的本地运行脚本未随包提供。

apidojo-io

热度 11.26

最近更新 2026-09-03 04:44:57

分类：营销依赖：第三方 API / 代码执行 / 读写文件应用场景：社交媒体 / 市场分析 / 报告撰写 / 研究

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add building-full-social-audit-for-brand

Metadata

name: building-full-social-audit-for-brand
description: Builds a comprehensive social media audit for a brand across all major platforms using apidojo's multi-platform scrapers. Triggers when the user asks to: do a social media audit for a brand, build a full social media presence report, analyze a brand's performance across all social platforms, create a cross-platform social media benchmark, audit a competitor's entire social media strategy, build a social media scorecard for a brand, or create a comprehensive social media analysis covering Twitter Instagram TikTok and YouTube. Returns per-platform metrics, follower counts, engagement rates, content mix, posting frequency, and overall brand health score. Ideal for social media managers, brand strategists, and agency teams doing comprehensive brand audits.
license: Apache-2.0
metadata: {"author":"apidojo","version":"1.0","apify-actors":"apidojo/twitter-user-scraper, apidojo/instagram-scraper, apidojo/tiktok-profile-scraper, apidojo/youtube-scraper"}

Building Full Social Audit For Brand

Executes building full social audit for brand using apidojo scrapers. Part of the apidojo intelligence skills library.

Prerequisites

APIFY_TOKEN environment 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: Define parameters
- [ ] Step 2: Run twitter-user-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output

Step 2: Run the Actor

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# 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 json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~twitter-user-scraper"
Input:
{
  "searchTerms": "@[BRAND_HANDLE]" (run per platform),
  "maxItems": 100
}

REST API fallback:

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}'

Wait for SUCCEEDED. Fetch dataset:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

Step 3: Classify Results

classification: STRONG (score > 4%) | AVERAGE (2-4%) | WEAK (1-2%) | MINIMAL (< 1%)

Step 4: Score Each Result

score = brand_social_score = avg(platform_engagement_rate * platform_weight) where weights: Twitter=0.20, Instagram=0.30, TikTok=0.30, YouTube=0.20

Step 5: Edge Cases

Brand may not be on all platforms — note absent platforms as strategic gaps; adjust weighted score to sum of present platforms only

Additional fallbacks:

< 20 results: Broaden search terms; remove secondary filters
No results: Verify the search terms are correct; try alternate phrasings
Data quality issues: Remove entries with missing key fields; note count in output

Output Format

# Building Full Social Audit For Brand
Results: [N] | Date: [DATE]

| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |

## Summary
Top result: [description]
Key finding: [insight]

Troubleshooting

Too few results: Broaden the primary search term; remove restrictive filters. Low quality results: Apply minimum score threshold (≥ 0.50) to filter noise. Actor fails to run: Verify API key; check actor status at apify.com/apidojo.