building-full-social-audit-for-brand — Claude Code skill
Audits brand profiles across Twitter, Instagram, TikTok, and YouTube via Apify scrapers. Computes engagement metrics and an aggregate brand health score.
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a claude-codeWhat building-full-social-audit-for-brand does
This skill inspects brand profiles across Twitter, Instagram, TikTok, and YouTube. The agent invokes dedicated Apify actors built by apidojo. It pulls follower counts and interaction rates into a structured table. Results fall into distinct tiers: MINIMAL for engagement below 1%, WEAK for 1-2%, AVERAGE for 2-4%, and STRONG when metrics exceed 4%.
Execution runs through node scripts/run_actor.js, an Apify MCP tool, or direct REST calls. A weighted formula calculates overall health: Instagram and TikTok carry 0.30 each, while Twitter and YouTube receive 0.20. Missing channels become strategic gaps. The skill then recalculates the weighted sum based solely on active profiles.
Running queries requires an APIFY_TOKEN in your environment or .env file. Without this credential, scraping calls fail immediately. If a search yields under 20 results, the agent strips secondary filters. A quality threshold of 0.50 discards low-value entries.
What it helps with
- Audit brand presence across Twitter, Instagram, TikTok, and YouTube
- Calculate weighted cross-platform engagement scores
- Benchmark competitor performance on social media
- Identify missing channels and strategic coverage gaps
Example prompts for the agent
- Run a full social audit for the brand across Twitter, Instagram, TikTok, and YouTube
- Analyze competitor performance and calculate the weighted brand score
- Build a social presence scorecard and identify platform coverage gaps
How to install building-full-social-audit-for-brand
1Skills CLI (Vercel)
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a claude-code2Manually: put the files in place
~/.claude/skills/building-full-social-audit-for-brand/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/building-full-social-audit-for-brand/
1Skills CLI (Vercel)
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a codex2Manually: put the files in place
.agents/skills/building-full-social-audit-for-brand/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a cursor2Manually: put the files in place
.cursor/skills/building-full-social-audit-for-brand/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install apidojo-io/apidojo-skills building-full-social-audit-for-brand2Manually: put the files in place
.github/skills/building-full-social-audit-for-brand/SKILL.md1Skills CLI (Vercel)
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a gemini-cli2Platform CLI
gemini skills install https://github.com/apidojo-io/apidojo-skills --path skills/intent/building-full-social-audit-for-brandManually: put the files in place
.devin/skills/building-full-social-audit-for-brand/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about building-full-social-audit-for-brand
How do I install building-full-social-audit-for-brand in Claude Code?
Run npx skills add apidojo-io/apidojo-skills --skill building-full-social-audit-for-brand -a claude-code.
What does building-full-social-audit-for-brand do?
It triggers Apify scrapers to collect metrics across four social networks, calculates engagement rates, and produces an evaluation table with a weighted brand score.
What is required to run the social audit scrapers?
You need an APIFY_TOKEN set in your environment or .env file. You can also configure an Apify MCP server to invoke the actors directly.
Source text
SKILL.md · Apache-2.0
---
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):**
```bash
# 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:**
```bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}'
```
Wait for `SUCCEEDED`. Fetch dataset:
```bash
curl "https://api.apify.com/v2/actor-runs/$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.
© apidojo · Apache-2.0 · apidojo-io/apidojo-skills