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apify-trend-analysis

Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.

读凭据写文件联网读文件严重 13 · 高危 1sickn33/agentic-awesome-skills

它会碰到什么

扫了多少2 个文本文件,16 KB
它会碰到什么读凭据写文件联网读文件
命中总数30 处
命中统计严重 13 · 高 1 · 中 9 · 低 7
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-paths
    node --env-file=.env scripts/run_actor.js --actor ACTOR_ID --input '{}'
  • 严重 reference/scripts/run_actor.js:83cred-paths
    node --env-file=.env scripts/run_actor.js \\
  • 严重 reference/scripts/run_actor.js:88cred-paths
    node --env-file=.env scripts/run_actor.js \\
  • 严重 reference/scripts/run_actor.js:324cred-paths
    console.error('Error: APIFY_TOKEN not found in .env file');
  • 严重 reference/scripts/run_actor.js:326cred-paths
    console.error('Add your token to .env file:');
  • 严重 SKILL.md:16cred-paths
    - `.env` file with `APIFY_TOKEN`
  • 严重 SKILL.md:64cred-paths
    export $(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:87cred-paths
    node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  • 严重 SKILL.md:94cred-paths
    node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  • 严重 SKILL.md:103cred-paths
    node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  • 严重 SKILL.md:121cred-paths
    `APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
  • reference/scripts/run_actor.js:322cred-envread
    const 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

Trend Analysis

Discover and track emerging trends using Apify Actors to extract data from multiple platforms.

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 trend type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings

Step 1: Identify Trend Type

Select the appropriate Actor based on research needs:

| User Need | Actor ID | Best For |

|-----------|----------|----------|

| Search trends | apify/google-trends-scraper | Google Trends data |

| Hashtag tracking | apify/instagram-hashtag-scraper | Hashtag content |

| Hashtag metrics | apify/instagram-hashtag-stats | Performance stats |

| Visual trends | apify/instagram-post-scraper | Post analysis |

| Trending discovery | apify/instagram-search-scraper | Search trends |

| Comprehensive tracking | apify/instagram-scraper | Full data |

| API-based trends | apify/instagram-api-scraper | API access |

| Engagement trends | apify/export-instagram-comments-posts | Comment tracking |

| Product trends | apify/facebook-marketplace-scraper | Marketplace data |

| Visual analysis | apify/facebook-photos-scraper | Photo trends |

| Community trends | apify/facebook-groups-scraper | Group monitoring |

| YouTube Shorts | streamers/youtube-shorts-scraper | Short-form trends |

| YouTube hashtags | streamers/youtube-video-scraper-by-hashtag | Hashtag videos |

| TikTok hashtags | clockworks/tiktok-hashtag-scraper | Hashtag content |

| Trending sounds | clockworks/tiktok-sound-scraper | Audio trends |

| TikTok ads | clockworks/tiktok-ads-scraper | Ad trends |

| Discover page | clockworks/tiktok-discover-scraper | Discover trends |

| Explore trends | clockworks/tiktok-explore-scraper | Explore content |

| Trending content | clockworks/tiktok-trends-scraper | Viral content |

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/google-trends-scraper).

This returns:

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

Step 3: Ask User Preferences

Before running, ask:

  1. 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
  1. 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 results found
  • File location and name
  • Key trend insights
  • Suggested next steps (deeper analysis, content opportunities)

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

When to Use

Use this skill when tackling tasks related to its primary domain or functionality as described above.

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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本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

同名技能的其他版本

有 3 个不同仓库或目录里都有叫 apify-trend-analysis 的技能。它们内容并不相同,别混用: