review-docs

作者: apify

审查Apify文档,确保其符合风格指南、质量标准及最佳实践。当用户说“审查此文档”、“检查此页面”、“审计…”时使用。

npx skills add https://github.com/apify/apify-docs --skill review-docs

Documentation review

Process

  1. Verify file version - git status to confirm you have the latest

  2. Run deterministic checks (main process) - these are objective, no judgment needed:

    • vale --minAlertLevel=suggestion "<file>" (prose style: voice, tone, terminology, grammar, headings, link text)
    • pnpm lint:md (heading hierarchy, list numbering, spacing)
    • .agents/skills/review-docs/scripts/check-frontmatter.sh "<file>" (description char count)

    Vale carries most of the style guide, so don't re-check its ground by hand. If it isn't installed, say so and note that prose coverage was skipped.

    For a pull request, run all three over every changed .md and .mdx file and report per file.

  3. Delegated review - spawn two subagents in parallel, for what no tool can check. Each reads the page being reviewed plus one standards file, and returns findings with line numbers and suggested fixes:

    • Subagent 1, standards/style-guide.md: bold outside UI elements and critical warnings, link text that doesn't say where it goes, non-parallel lists, missing serial commas, and loose use of "legacy", "alternative", or "deprecated"
    • Subagent 2, standards/page-structure.md: stacked headings, concepts used before they're explained, screenshots that don't earn their place or break the treatment rules, admonitions that don't fit their content, outnumber one per H2 section, or carry content the prose needs
  4. Content review (main process) - focus on what neither tools nor standards cover:

    • Content structure (clear intro, logical flow, next steps)
    • Technical accuracy (code examples correct, API endpoints current)
    • Completeness (prerequisites listed, edge cases covered)
    • Code example quality (complete, runnable, commented where needed)
  5. Format output - per .agents/skills/review-docs/references/review-format.md. Tool output goes in its own section, verbatim with rule names and line numbers. Judgment findings go in a separate section and must not restate anything a tool reported.

For detailed process notes and edge cases, see .agents/skills/review-docs/references/process.md.

来自 apify 的更多技能

apify-influencer-brand-collabs
apify
通过串联Apify Actors发现Instagram品牌与创作者的合作关系。当用户询问某品牌与谁合作、某创作者曾与哪些品牌进行付费合作时使用…
apify-actor-development
apify
创建、调试和部署用于网页抓取、自动化及数据处理的无服务器云程序。支持JavaScript、TypeScript和Python模板,集成Crawlee、Playwright和Cheerio库,用于HTTP和基于浏览器的爬取。包含通过apify run进行的本地测试(使用隔离存储)、输入/输出的模式验证,以及通过apify push部署到Apify平台。需要Apify CLI认证,并在.actor/actor.json中强制包含generatedBy元数据以用于AI...
apify-actorization
apify
将现有项目转换为无服务器Apify Actors,支持语言特定的SDK集成。支持JavaScript/TypeScript(使用Actor.init() / Actor.exit())、Python(异步上下文管理器)以及通过CLI包装器的任何语言。提供结构化工作流:使用apify init搭建脚手架,应用SDK封装,配置输入/输出模式,通过apify run进行本地测试,然后使用apify push进行部署。包含输入和输出模式验证、Docker容器化以及可选的按事件付费...
apify-content-analytics
apify
通过Apify Actors实现多平台内容分析,支持Instagram、Facebook、YouTube和TikTok。涵盖17+个专业Actors,覆盖所有四个平台的帖子、Reels、故事、评论、话题标签、粉丝和广告。使用mcpc CLI动态获取Actor模式,以确定所需输入和可用输出字段。结果以三种格式输出:快速聊天显示、CSV导出或JSON导出,并可自定义结果数量。需要在.env文件中配置Apify令牌,并安装Node.js 20.6+...
apify-ecommerce
apify
从50多个电商平台提取产品数据、价格、评论和卖家信息。三种工作模式:产品与定价(价格追踪、竞品分析)、客户评论(情感分析、质量问题)和卖家情报(通过Google Shopping发现供应商)。支持亚马逊(20多个地区)、沃尔玛、eBay、宜家、好市多及欧洲零售商;可通过产品链接、分类链接或关键词搜索输入。可选AI驱动分析生成价格洞察...
apify-generate-output-schema
apify
通过分析Apify Actor的源代码生成输出模式(dataset_schema.json、output_schema.json、key_value_store_schema.json)。在以下情况下使用…
apify-influencer-discovery
apify
使用Apify Actors在Instagram、Facebook、YouTube和TikTok上发现并评估网红。将发现请求路由至15+个专业Actors,涵盖所有主流平台的个人资料抓取、标签搜索、互动分析和细分领域发现。通过mcpc动态获取Actor模式,在执行前确定所需输入和可用输出字段。支持三种导出模式:内联聊天显示、CSV或JSON文件输出,并可自定义结果数量...
apify-ultimate-scraper
apify
自动化网页抓取工具,为55多个平台(包括Instagram、TikTok、YouTube、Facebook、Google Maps等)选择最优Actor。涵盖8大主流平台的55多个预配置Actor,并提供针对特定用例的选择指导(潜在客户生成、网红发现、品牌监控、竞争对手分析、趋势研究)。支持三种输出格式:快速聊天显示、CSV导出或JSON导出,可自定义结果数量限制。包含多Actor工作流模式,适用于复杂...