通过检查代码、目标和限制,评估新的或现有的 AI 项目;核对可用目录中的技能后提出建议,并制定包含依赖关系、完成条件和检查方式的任务清单与实施计划。
- 规划新 AI 项目的启动
- 梳理现有项目的技术问题
- 从可用目录中挑选技能
使用 Apify Actors 从地图、旅游和社交平台收集评论、评分及品牌提及。可在聊天中查看部分结果,也可将完整数据导出为 CSV 或 JSON,用于了解品牌口碑。
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
实测评分 未实测
查看安装方法此技能会从地图、旅游和社交平台收集评论、评分及品牌提及,并整理成可供查看口碑的资料。它会根据目标选择合适的 Apify Actor,查看输入项后再运行。可收集 Google Maps、Booking.com、TripAdvisor 的评论,也可收集 Instagram、YouTube、TikTok 等平台的评论。少量结果可以显示在聊天中,全部结果则可导出为 CSV 或 JSON。
当您想了解店铺或酒店的评价,或调查社交平台上人们如何谈论某个品牌时,可以使用此技能。收集完成后,它会整理结果数量、可用字段和保存位置,并可建议后续进行情感分析或筛选。
需要在 .env 中设置 APIFY_TOKEN,并安装 Node.js 20.6 或更高版本及 mcpc CLI。运行前请确定输出格式和结果数量,并确认所选 Actor 的输入条件适用于目标平台。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月24日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
Verify prerequisites before any paid run.
.env file with APIFY_TOKEN--env-file support).env untracked and private; configure the token locally without pasting it into chat or command arguments.Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Determine data source (select Actor)
- [ ] Step 2: Fetch Actor schema via an approved connector or Console
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the monitoring script
- [ ] Step 5: Summarize results
Select the appropriate Actor based on user needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Google Maps reviews | compass/crawler-google-places | Business reviews, ratings |
| Google Maps review export | compass/Google-Maps-Reviews-Scraper | Dedicated review scraping |
| Booking.com hotels | voyager/booking-scraper | Hotel data, scores |
| Booking.com reviews | voyager/booking-reviews-scraper | Detailed hotel reviews |
| TripAdvisor reviews | maxcopell/tripadvisor-reviews | Attraction/restaurant reviews |
| Facebook reviews | apify/facebook-reviews-scraper | Page reviews |
| Facebook comments | apify/facebook-comments-scraper | Post comment monitoring |
| Facebook page metrics | apify/facebook-pages-scraper | Page ratings overview |
| Facebook reactions | apify/facebook-likes-scraper | Reaction type analysis |
| Instagram comments | apify/instagram-comment-scraper | Comment sentiment |
| Instagram hashtags | apify/instagram-hashtag-scraper | Brand hashtag monitoring |
| Instagram search | apify/instagram-search-scraper | Brand mention discovery |
| Instagram tagged posts | apify/instagram-tagged-scraper | Brand tag tracking |
| Instagram export | apify/export-instagram-comments-posts | Bulk comment export |
| Instagram comprehensive | apify/instagram-scraper | Full Instagram monitoring |
| Instagram API | apify/instagram-api-scraper | API-based monitoring |
| YouTube comments | streamers/youtube-comments-scraper | Video comment sentiment |
| TikTok comments | clockworks/tiktok-comments-scraper | TikTok sentiment |
Inspect the current Actor details and input schema using the authenticated Apify connector available in the session, or its Console page. Discover actual tool names and parameters before calling them. Do not parse .env with shell substitution or pass a token as a CLI header argument. Treat the Actor table as discovery candidates, not verified availability or schemas.
This returns:
Before running, ask:
Quick answer (display in chat, no file):
node --env-file=.env "<resolved-skill-directory>/reference/scripts/run_actor.js" \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'
CSV:
node --env-file=.env "<resolved-skill-directory>/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 "<resolved-skill-directory>/reference/scripts/run_actor.js" \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format json
After completion, report:
APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token
Connector unavailable - Inspect the schema through the Console; do not claim an unavailable tool was called.
Actor not found - Check Actor ID spelling
Run FAILED - Ask user to check Apify console link in error output
Timeout - The local timeout does not abort the remote run. Inspect the printed run ID in Console before retrying to avoid duplicate charges.
Before launch, confirm the selected Actor, authorized public-data scope, current input schema, result limits and pricing with the user’s request. Respect source terms and access controls; do not collect private group data or unnecessary personal contact information. Start with a small Actor-supported input limit. --max-items limits downloaded output only (default 1000); it does not cap Actor work or billing. The helper sends a skill-identifying User-Agent to Apify. Resolve the installed skill directory in the command placeholders. Output files must be new paths; exports preserve long values and heterogeneous fields. Quick answers fetch at most five records; minimize or redact personal fields before sharing.
Deduplicate reviews by platform and stable ID, record rating scale and retrieval time, and distinguish source rating from inferred sentiment. Counts from different platforms are not comparable without coverage and scale definitions. Preserve negative, neutral and uncertain cases; validate language/sarcasm on a small human-reviewed sample before labeling a trend. A single scrape is a snapshot, not continuous monitoring; scheduling and notifications require an actual configured service and authorized destination. Do not post replies, contact reviewers or remove content as part of data collection.
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通过检查代码、目标和限制,评估新的或现有的 AI 项目;核对可用目录中的技能后提出建议,并制定包含依赖关系、完成条件和检查方式的任务清单与实施计划。
检查代码和基础设施中的安全风险,梳理潜在威胁并规划防护改进。涵盖 OWASP 检查、攻击与防御验证及事件响应;操作范围需获明确授权,并结合具体环境验证结果。
将重复任务整理成 Andru.ia 技能,明确输入、输出、示例和限制;编写 `SKILL.md`,检查目录结构和验证要求,并准备供审阅的拉取请求。
项目行业确定后,整理行业背景、可能适用的法规、用户熟悉的界面模式、技术选择和风险,并区分已核实事实、假设及待专家确认的事项。
通过 2slides API 将文本、提纲或文档制作为演示稿,可参考图片风格、选择主题、添加人工智能旁白,并导出幻灯片图片或音频。
规划360度评估或同伴反馈流程,并根据已确认的需求创建空白答复台账。可生成字段一致的CSV、SQL、JSON Schema或Notion属性映射,并将可见范围与评分配置分开整理。