How do I install the Building Full Social Audit For Brand skill?

Run npx skillmds@latest add apidojo-io/building-full-social-audit-for-brand in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Building Full Social Audit For Brand safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Building Full Social Audit For Brand?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Building Full Social Audit For Brand free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Building Full Social Audit For Brand?

apidojo-io (@apidojo-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Building Full Social Audit For Brand by apidojo-io

Name: Building Full Social Audit For Brand
Author: apidojo-io

Building Full Social Audit For Brand

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.

apidojo-io Updated Sep 17, 2026

File contents

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.

---name: building-full-social-audit-for-branddescription: 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---# Building Full Social Audit For BrandExecutes 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 CSVnode scripts/run_actor.js \ --actor "apidojo~twitter-user-scraper" \ --input '{"param": "value"}' \ --output YYYY-MM-DD_results.csv --format csv# Save as JSONnode 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-actorActor: "apidojo~twitter-user-scraper"Input:{ "searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}```**REST API fallback:**```bashcurl -X POST \ "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}'```Wait for `SUCCEEDED`. Fetch dataset:```bashcurl "https://api.apify.com/v2/actor-runs/$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 BrandResults: [N] | Date: [DATE]| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] ||---|------------|-----------|-----------|-----------------|---------|| 1 | [value] | [value] | [value] | [type] | [0.XX] |## SummaryTop 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.

Frequently asked questions

Building Full Social Audit For Brand

File contents

Building Full Social Audit For Brand

Prerequisites

Inputs

Workflow

Step 2: Run the Actor

Step 3: Classify Results

Step 4: Score Each Result

Step 5: Edge Cases

Output Format

Troubleshooting

Related skills

Frequently asked questions

How do I install the Building Full Social Audit For Brand skill?

What does the Building Full Social Audit For Brand skill do?

Is Building Full Social Audit For Brand safe to use?

Which AI agents work with Building Full Social Audit For Brand?

Is Building Full Social Audit For Brand free to use?

Who published Building Full Social Audit For Brand?