apify-content-analytics
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
它会碰到什么
逐条看命中(14 条严重或高危)
- 严重
reference/scripts/run_actor.js:7cred-paths* node --env-file=.env scripts/run_actor.js --actor ACTOR_ID --input '{}' - 严重
reference/scripts/run_actor.js:10cred-paths* node --env-file=.env scripts/run_actor.js --actor ACTOR_ID --input '{}' --output leads.csv --format csv - 严重
reference/scripts/run_actor.js:65cred-pathsnode --env-file=.env scripts/run_actor.js --actor ACTOR_ID --input '{}' - 严重
reference/scripts/run_actor.js:83cred-pathsnode --env-file=.env scripts/run_actor.js \\
- 严重
reference/scripts/run_actor.js:88cred-pathsnode --env-file=.env scripts/run_actor.js \\
- 严重
reference/scripts/run_actor.js:324cred-pathsconsole.error('Error: APIFY_TOKEN not found in .env file'); - 严重
reference/scripts/run_actor.js:326cred-pathsconsole.error('Add your token to .env file:'); - 严重
SKILL.md:21cred-paths- `.env` file with `APIFY_TOKEN`
- 严重
SKILL.md:67cred-pathsexport $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_
- 严重
SKILL.md:90cred-pathsnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ - 严重
SKILL.md:97cred-pathsnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ - 严重
SKILL.md:106cred-pathsnode --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ - 严重
SKILL.md:123cred-paths`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
- 高
reference/scripts/run_actor.js:322cred-envreadconst token = process.env.APIFY_TOKEN;
这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。
技能内容
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)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI 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.
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它属于哪个仓库
skills/apify-content-analytics/SKILL.md同一个仓库里的其他技能
同名技能的其他版本
有 3 个不同仓库或目录里都有叫 apify-content-analytics 的技能。它们内容并不相同,别混用:
- sickn33/agentic-awesome-skills — Track engagement metrics, measure campaign ROI, and analyze content performance across Ins
- sickn33/agentic-awesome-skills — Track engagement metrics, measure campaign ROI, and analyze content performance across Ins