apify-content-analytics

sickn33/agentic-awesome-skills · plugins/agentic-awesome-skills-claude/skills/apify-content-analytics/SKILL.md

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

Data & AINo license★ 45496⑂ 6664commit 5cf4dfe

Install skillView source on GitHub

What this skill does

Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

When to Use

You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
The task is to use Apify Actors to collect cross-platform content performance data.
You need exported analytics results and a concise interpretation of what content is performing best.

Prerequisites

(No need to check it upfront)

.env file with APIFY_TOKEN
Node.js 20.6+ (for native --env-file support)
mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings

Step 1: Identify Content Analytics Type

Select the appropriate Actor based on analytics needs:

| User Need | Actor ID | Best For | |-----------|----------|----------| | Post engagement metrics | apify/instagram-post-scraper | Post performance | | Reel performance | apify/instagram-reel-scraper | Reel analytics | | Follower growth tracking | apify/instagram-followers-count-scraper | Growth metrics | | Comment engagement | apify/instagram-comment-scraper | Comment analysis | | Hashtag performance | apify/instagram-hashtag-scraper | Branded hashtags | | Mention tracking | apify/instagram-tagged-scraper | Tag tracking | | Comprehensive metrics | apify/instagram-scraper | Full data | | API-based analytics | apify/instagram-api-scraper | API access | | Facebook post performance | apify/facebook-posts-scraper | Post metrics | | Reaction analysis | apify/facebook-likes-scraper | Engagement types | | Facebook Reels metrics | apify/facebook-reels-scraper | Reels performance | | Ad performance tracking | apify/facebook-ads-scraper | Ad analytics | | Facebook comment analysis | apify/facebook-comments-scraper | Comment engagement | | Page performance audit | apify/facebook-pages-scraper | Page metrics | | YouTube video metrics | streamers/youtube-scraper | Video performance | | YouTube Shorts analytics | streamers/youtube-shorts-scraper | Shorts performance | | TikTok content metrics | clockworks/tiktok-scraper | TikTok analytics |

Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., apify/instagram-post-scraper).

This returns:

Actor description and README
Required and optional input parameters
Output fields (if available)

Step 3: Ask User Preferences

Before running, ask:

Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

Step 5: Summarize Findings

After completion, report:

Number of content pieces analyzed
File location and name
Key performance insights
Suggested next steps (deeper analysis, content optimization)

Error Handling

APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token mcpc not found - Ask user to install npm install -g @apify/mcpc Actor not found - Check Actor ID spelling Run FAILED - Ask user to check Apify console link in error output Timeout - Reduce input size or increase --timeout

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Installation

Copy a source-pinned command for your client. You run it yourself.

Destination: .claude/skills/apify-content-analytics · pinned to the source commit

# Run from your project root
git clone https://github.com/sickn33/agentic-awesome-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 5cf4dfeb13ea966daa1e117897689cd7991e3f44
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/plugins/agentic-awesome-skills-claude/skills/apify-content-analytics" ".claude/skills/"
rm -rf .skillboard-tmp

Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.

New here? Step-by-step setup – from installing the agent to using the skill

Operating systemAgentI already use Claude Code

1
Install Git
Install Git with your package manager (Debian/Ubuntu shown; use dnf/pacman on others). Official download.
```
sudo apt update && sudo apt install -y git
```
2
Install Claude Code
Requires Node.js 18+. Install the CLI globally: Official docs. (command-line tool)
```
npm install -g @anthropic-ai/claude-code
```

Get the skill, pinned to its exact version

Open a terminal and run these steps (they clone the source, check out the exact commit, and copy the skill into place):

# Run from your project root
git clone https://github.com/sickn33/agentic-awesome-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 5cf4dfeb13ea966daa1e117897689cd7991e3f44
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/plugins/agentic-awesome-skills-claude/skills/apify-content-analytics" ".claude/skills/"
rm -rf .skillboard-tmp

Destination: .claude/skills/apify-content-analytics

4
Use it in Claude Code
Open Claude Code in your project. It reads skills from the folder above, so apify-content-analytics is now available. Always review the source before using it – static checks cannot prove runtime safety.

Security & Audits

Scanner static-checks@0.1.0 · commit 5cf4dfeb13ea. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.

highCredential or secret access
References credentials, tokens or secret files that a skill should not need.
Evidence: [redacted]· fingerprint e9cbb0224c4a3d23
mediumShell or process execution
Instructs shell/process/package operations that run commands on the host.
Evidence: npm install· fingerprint 3a2dc0ae21eb56d7

apify-content-analytics

sickn33/agentic-awesome-skills · plugins/agentic-awesome-skills-claude/skills/apify-content-analytics/SKILL.md

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

Data & AINo license★ 45496⑂ 6664commit 5cf4dfe

Install skillView source on GitHub

What this skill does

Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

When to Use

You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
The task is to use Apify Actors to collect cross-platform content performance data.
You need exported analytics results and a concise interpretation of what content is performing best.

Prerequisites

(No need to check it upfront)

.env file with APIFY_TOKEN
Node.js 20.6+ (for native --env-file support)
mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings

Step 1: Identify Content Analytics Type

Select the appropriate Actor based on analytics needs:

Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., apify/instagram-post-scraper).

This returns:

Actor description and README
Required and optional input parameters
Output fields (if available)

Step 3: Ask User Preferences

Before running, ask:

Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

Step 5: Summarize Findings

After completion, report:

Number of content pieces analyzed
File location and name
Key performance insights
Suggested next steps (deeper analysis, content optimization)

Error Handling

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Installation

Copy a source-pinned command for your client. You run it yourself.

Destination: .claude/skills/apify-content-analytics · pinned to the source commit

# Run from your project root
git clone https://github.com/sickn33/agentic-awesome-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 5cf4dfeb13ea966daa1e117897689cd7991e3f44
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/plugins/agentic-awesome-skills-claude/skills/apify-content-analytics" ".claude/skills/"
rm -rf .skillboard-tmp

Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.

New here? Step-by-step setup – from installing the agent to using the skill

Operating systemAgentI already use Claude Code

1
Install Git
Install Git with your package manager (Debian/Ubuntu shown; use dnf/pacman on others). Official download.
```
sudo apt update && sudo apt install -y git
```
2
Install Claude Code
Requires Node.js 18+. Install the CLI globally: Official docs. (command-line tool)
```
npm install -g @anthropic-ai/claude-code
```

Get the skill, pinned to its exact version

Open a terminal and run these steps (they clone the source, check out the exact commit, and copy the skill into place):

# Run from your project root
git clone https://github.com/sickn33/agentic-awesome-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 5cf4dfeb13ea966daa1e117897689cd7991e3f44
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/plugins/agentic-awesome-skills-claude/skills/apify-content-analytics" ".claude/skills/"
rm -rf .skillboard-tmp

Destination: .claude/skills/apify-content-analytics

4
Use it in Claude Code
Open Claude Code in your project. It reads skills from the folder above, so apify-content-analytics is now available. Always review the source before using it – static checks cannot prove runtime safety.

Security & Audits

Scanner static-checks@0.1.0 · commit 5cf4dfeb13ea. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.

highCredential or secret access
References credentials, tokens or secret files that a skill should not need.
Evidence: [redacted]· fingerprint e9cbb0224c4a3d23
mediumShell or process execution
Instructs shell/process/package operations that run commands on the host.
Evidence: npm install· fingerprint 3a2dc0ae21eb56d7

apify-content-analytics

What this skill does

Content Analytics

When to Use

Prerequisites

Workflow

Step 1: Identify Content Analytics Type

Step 2: Fetch Actor Schema

Step 3: Ask User Preferences

Step 4: Run the Script

Step 5: Summarize Findings

Error Handling

Limitations

Installation

Install Git

Install Claude Code

Get the skill, pinned to its exact version

Use it in Claude Code

Security & Audits

apify-content-analytics

What this skill does

Content Analytics

When to Use

Prerequisites

Workflow

Step 1: Identify Content Analytics Type

Step 2: Fetch Actor Schema

Step 3: Ask User Preferences

Step 4: Run the Script

Step 5: Summarize Findings

Error Handling

Limitations

Installation

Install Git

Install Claude Code

Get the skill, pinned to its exact version

Use it in Claude Code

Security & Audits