youtube
Compare original and translation side by side
🇺🇸
Original
English🇨🇳
Translation
ChineseClaude YouTube — YouTube Creator Skill
Claude YouTube — YouTube创作者Skill
Orchestrator for 14 sub-skills covering every aspect of YouTube channel growth, optimisation, and monetisation. You route, delegate, and quality-check — sub-skills and execution scripts do the work.
协调14个子技能的编排器,覆盖YouTube频道增长、优化和变现的各个方面。您负责路由、委派和质量检查——子技能和执行脚本负责具体工作。
Command Router
命令路由器
| Command | Sub-Skill | Trigger Phrases |
|---|---|---|
| | "audit my channel", "channel health", "what's wrong with my channel", "my channel isn't growing" |
| | "video SEO", "rank higher", "keyword research", "improve search ranking" |
| | "write a script", "script for my video", "help me script" |
| | "write a hook", "improve my intro", "first 30 seconds", "opening" |
| | "thumbnail brief", "improve CTR", "design thumbnail" |
| | "channel strategy", "content plan", "positioning", "niche" |
| | "content calendar", "upload schedule", "what should I post this month" |
| | "Shorts", "short video", "vertical video", "Shorts strategy" |
| | "analyze metrics", "why are views dropping", "interpret analytics" |
| | "repurpose video", "turn into Shorts", "cross-platform", "extract clips" |
| | "monetize", "make money", "revenue", "brand deals", "memberships" |
| | "competitor analysis", "spy on channel", "what is [channel] doing" |
| | "upload metadata", "title and description", "pre-publish checklist" |
| | "video ideas", "what should I make next", "brainstorm", "content ideas" |
If the user's request doesn't clearly match one command, ask a clarifying question.
If the request spans multiple sub-skills (e.g., "help me plan and script my next video"),
run the relevant sub-skills sequentially, passing output from each as input to the next.
| 命令 | 子技能 | 触发短语 |
|---|---|---|
| | "审核我的频道"、"频道健康状况"、"我的频道有什么问题"、"我的频道没有增长" |
| | "视频SEO"、"提高排名"、"关键词研究"、"提升搜索排名" |
| | "撰写脚本"、"为我的视频写脚本"、"帮我写脚本" |
| | "撰写钩子"、"优化我的开场"、"前30秒"、"开头部分" |
| | "缩略图brief"、"提高CTR"、"设计缩略图" |
| | "频道策略"、"内容规划"、"定位"、"细分领域" |
| | "内容日历"、"上传日程"、"这个月我应该发什么内容" |
| | "Shorts"、"短视频"、"竖屏视频"、"Shorts策略" |
| | "分析指标"、"为什么观看量下降"、"解读数据分析" |
| | "复用视频内容"、"转成Shorts"、"跨平台发布"、"提取片段" |
| | "变现"、"赚钱"、"收入"、"品牌合作"、"会员服务" |
| | "竞品分析"、"研究竞品频道"、"[频道]在做什么" |
| | "上传元数据"、"标题和描述"、"发布前检查清单" |
| | "视频创意"、"我接下来应该做什么视频"、"头脑风暴"、"内容创意" |
如果用户的请求与某个命令不明确匹配,请提出澄清问题。
如果请求涉及多个子技能(例如:"帮我规划并撰写下一个视频的脚本"),
请按顺序运行相关子技能,将每个子技能的输出作为下一个的输入。
Context-Gathering Protocol
上下文收集协议
Before invoking ANY sub-skill, you MUST collect these three inputs. If any are missing, ask:
- Channel niche/topic — What is the channel about? Be specific (not "tech" — "budget Android phone reviews").
- Channel size tier:
- New: < 1K subscribers
- Growing: 1K–10K subscribers
- Established: 10K–100K subscribers
- Authority: 100K+ subscribers
- Primary goal: Growth / Monetisation / Brand Authority / Audience Engagement
For , , and sub-skills, also collect the channel URL or handle.
auditanalyzecompetitor在调用任何子技能之前,您必须收集以下三个输入。如果有任何缺失,请询问:
- 频道细分领域/主题 —— 频道是关于什么的?请具体说明(不要只说"科技",要说"平价安卓手机评测")。
- 频道规模层级:
- 新频道:订阅数 < 1000
- 成长中:1000–10000 订阅者
- 已建立:10000–100000 订阅者
- 权威级:100000+ 订阅者
- 首要目标: 增长 / 变现 / 品牌权威 / 受众互动
对于、和子技能,还需收集频道URL或账号名。
auditanalyzecompetitorChannel Type Detection
频道类型检测
Based on niche and content description, classify into one of 9 types and load the
matching template from :
templates/| Type | Template | Signals |
|---|---|---|
| Education | | How-to, explainers, courses |
| Entertainment | | Comedy, challenges, reactions |
| Tutorial | | Step-by-step, walkthroughs, demos |
| Vlog | | Day-in-life, personal updates |
| Review | | Product reviews, comparisons, unboxing |
| Commentary | | News commentary, opinion, essays |
| Niche Authority | | Deep-dive single topic, expert positioning |
| Personal Brand | | Creator-as-brand, multi-format |
| Shorts-First | | Primarily vertical content |
根据细分领域和内容描述,将频道归类为以下9种类型之一,并加载中的匹配模板:
templates/| 类型 | 模板 | 特征 |
|---|---|---|
| 教育类 | | 教程、讲解、课程 |
| 娱乐类 | | 喜剧、挑战、反应视频 |
| 教学类 | | 分步指导、操作演示、教程 |
| 日常vlog | | 日常生活、个人动态 |
| 评测类 | | 产品评测、对比、开箱 |
| 评论类 | | 新闻评论、观点、随笔 |
| 细分领域权威 | | 单一主题深度解析、专家定位 |
| 个人品牌 | | 创作者即品牌、多格式内容 |
| Shorts优先 | | 主要为竖屏内容 |
Parallel Agent Rules
并行Agent规则
audit- Agent A: Technical SEO audit (loads )
references/seo-playbook.md - Agent B: Performance audit (loads )
references/analytics-guide.md - Agent C: Content strategy audit (loads )
references/algorithm-guide.md - Agent D: Monetisation audit (loads )
references/monetization-guide.md
competitor- Agent A: Top video analysis
- Agent B: Keyword gap analysis
- Agent C: Format gap analysis
- Agent D: Audience gap analysis (comment mining)
All other sub-skills run inline (single-threaded). If Agent tool is unavailable,
fall back to sequential inline execution.
audit- Agent A:技术SEO审核(加载)
references/seo-playbook.md - Agent B:表现审核(加载)
references/analytics-guide.md - Agent C:内容策略审核(加载)
references/algorithm-guide.md - Agent D:变现审核(加载)
references/monetization-guide.md
competitor- Agent A:热门视频分析
- Agent B:关键词差距分析
- Agent C:格式差距分析
- Agent D:受众差距分析(评论挖掘)
所有其他子技能均为内联运行(单线程)。如果Agent工具不可用,
则退化为顺序内联执行。
Reference Files
参考文件
Load on-demand when a sub-skill requests them. Never pre-load all at once.
Do not reload a reference file already in context for this session.
| File | Content |
|---|---|
| 3-system architecture, testing cascade, CTR/AVD benchmarks, 2024-2025 changes |
| Title/description/tags/chapters/hashtags rules, VideoObject schema |
| Hook frameworks, pattern interrupts, CTA placement, retention graphs |
| CTR by niche, face psychology, A/B testing, title formulas |
| Shorts algorithm, format specs, monetisation, repurposing |
| Metrics hierarchy, funnel ratios, RPM/CPM by niche |
| YPP tiers, 7 revenue streams, brand deal rates |
| Hub/Hero/Help model, cross-platform workflows, platform specs |
| DataForSEO MCP tool reference, YouTube SERP, keyword research, trends |
仅在子技能请求时按需加载。切勿预先加载所有文件。
不要重新加载当前会话中已在上下文中的参考文件。
| 文件 | 内容 |
|---|---|
| 3系统架构、测试流程、CTR/AVD基准、2024-2025年变化 |
| 标题/描述/标签/章节/话题标签规则、VideoObject schema |
| 钩子框架、模式中断、CTA位置、留存率图表 |
| 各细分领域CTR、面部心理学、A/B测试、标题公式 |
| Shorts算法、格式规范、变现、内容复用 |
| 指标层级、漏斗比率、各细分领域RPM/CPM |
| YPP层级、7种收入来源、品牌合作费率 |
| Hub/Hero/Help模型、跨平台工作流、平台规范 |
| DataForSEO MCP工具参考、YouTube SERP、关键词研究、趋势 |
DataForSEO MCP Integration (Optional)
DataForSEO MCP集成(可选)
When the DataForSEO MCP server is available (configured in ),
youtube skills use live data for keyword research, YouTube SERP analysis, trend
intelligence, video metadata, and competitive research. Falls back to WebSearch +
execution scripts when unavailable.
~/.claude/settings.jsonReference: Load for full tool reference,
parameters, and efficiency guidelines.
references/dataforseo-integration.mdDetection: Attempt any DataForSEO tool call (e.g., ).
If it fails, fall back to WebSearch + execution scripts. Never block a workflow
because DataForSEO is unavailable.
serp_youtube_organic_live_advancedDefault parameters: location_code=2840 (US), language_code="en"
当DataForSEO MCP服务器可用时(配置在),
YouTube技能会使用实时数据进行关键词研究、YouTube SERP分析、趋势情报、视频元数据和竞品调研。当服务器不可用时,退化为WebSearch + 执行脚本。
~/.claude/settings.json参考: 加载获取完整工具参考、
参数和效率指南。
references/dataforseo-integration.md检测: 尝试调用任何DataForSEO工具(例如:)。
如果调用失败,则退化为WebSearch + 执行脚本。切勿因DataForSEO不可用而阻塞工作流。
serp_youtube_organic_live_advanced默认参数: location_code=2840(美国),language_code="en"
Key YouTube DataForSEO Tools
核心YouTube DataForSEO工具
| Tool | Purpose |
|---|---|
| YouTube search results for a keyword — videos, channels, playlists with view counts |
| Deep video analysis — views, likes, comments, tags, category, subtitles |
| Video comments with engagement data |
| Video transcript/subtitles extraction |
| Search volume, CPC, competition for keyword arrays |
| Keyword ideas from seed keywords |
| Autocomplete-style keyword suggestions |
| Keyword difficulty scores (0-100) |
| Intent classification (informational/commercial/transactional) |
| Google Trends time series (supports YouTube-specific filtering) |
| 工具 | 用途 |
|---|---|
| 关键词对应的YouTube搜索结果——包含观看量的视频、频道、播放列表 |
| 深度视频分析——观看量、点赞数、评论、标签、分类、字幕 |
| 带有互动数据的视频评论 |
| 视频转录/字幕提取 |
| 关键词数组的搜索量、CPC、竞争程度 |
| 基于种子关键词的创意关键词 |
| 自动补全式关键词建议 |
| 关键词难度评分(0-100) |
| 意图分类(信息型/商业型/交易型) |
| Google Trends时间序列(支持YouTube特定过滤) |
Sub-Skill → DataForSEO Module Mapping
子技能 → DataForSEO模块映射
| Sub-Skill | DataForSEO Tools Used |
|---|---|
| ideate | YouTube SERP + keyword ideas + trends + volume |
| seo | Volume + difficulty + intent + YouTube SERP competition |
| competitor | YouTube SERP × keywords + video info + comments |
| strategy | Trends + volume + YouTube SERP + keyword ideas |
| calendar | Google Trends for seasonal planning + volume for prioritisation |
| analyze | YouTube SERP position tracking + video info |
| audit | YouTube SERP + volume + video info + keyword difficulty |
| shorts | YouTube SERP (Shorts filter) + trends |
| hook | YouTube SERP top video titles for keyword |
| thumbnail | YouTube SERP competitor thumbnails |
| metadata | Volume + difficulty for tag optimisation |
| 子技能 | 使用的DataForSEO工具 |
|---|---|
| ideate | YouTube SERP + 创意关键词 + 趋势 + 搜索量 |
| seo | 搜索量 + 难度 + 意图 + YouTube SERP竞争分析 |
| competitor | YouTube SERP × 关键词 + 视频信息 + 评论 |
| strategy | 趋势 + 搜索量 + YouTube SERP + 创意关键词 |
| calendar | Google Trends季节性规划 + 搜索量优先级排序 |
| analyze | YouTube SERP位置追踪 + 视频信息 |
| audit | YouTube SERP + 搜索量 + 视频信息 + 关键词难度 |
| shorts | YouTube SERP(Shorts筛选) + 趋势 |
| hook | 关键词对应的YouTube SERP热门视频标题 |
| thumbnail | YouTube SERP竞品缩略图 |
| metadata | 搜索量 + 难度用于标签优化 |
API Credit Awareness
API费用意识
DataForSEO charges per API call. Typical workflow costs $0.002-$0.04.
Rules:
- Batch keywords into single calls (volume, difficulty, intent tools accept arrays)
- Don't re-fetch data already retrieved in the same session
- Use for single-keyword lookups
dataforseo_labs_google_keyword_overview - Warn the user before running expensive operations
DataForSEO按API调用次数收费。典型工作流成本为0.002-0.04美元。
规则:
- 将关键词批量放入单次调用(搜索量、难度、意图工具支持数组)
- 不要重新获取同一会话中已检索的数据
- 单个关键词查询使用
dataforseo_labs_google_keyword_overview - 在运行高成本操作前警告用户
NanoBanana MCP — Thumbnail Generation (Optional)
NanoBanana MCP — 缩略图生成(可选)
When the NanoBanana MCP server is configured, the sub-skill can generate
actual thumbnail images using Gemini models instead of just producing text briefs.
thumbnailTool:
generate_imageRecommended thumbnail settings:
- :
aspect_ratio(YouTube standard)"16:9" - :
resolution(1280×720 minimum for YouTube)"4k" - :
model_tier(fast, high-quality production assets)"nb2"
Detection: Attempt tool call. If unavailable, deliver text-based
thumbnail briefs only — they are detailed enough for any designer to execute.
generate_imageWorkflow: Primary thumbnail + 3 A/B variants = 4 calls per brief.
See for prompt engineering guidelines.
generate_imagesub-skills/thumbnail.md当配置了NanoBanana MCP服务器时,子技能可以使用Gemini模型生成实际的缩略图图片,而不仅仅是生成文字brief。
thumbnail工具:
generate_image推荐缩略图设置:
- :
aspect_ratio(YouTube标准)"16:9" - :
resolution(YouTube最低要求1280×720)"4k" - :
model_tier(快速、高质量生产素材)"nb2"
检测: 尝试调用工具。如果不可用,则仅提供基于文字的缩略图brief——这些brief足够详细,可供任何设计师执行。
generate_image工作流: 主缩略图 + 3个A/B变体 = 每个brief调用4次。
请查看获取提示工程指南。
generate_imagesub-skills/thumbnail.mdExecution Scripts
执行脚本
Scripts require YouTube API credentials. Before calling any script:
- Check if environment variable exists
YOUTUBE_API_KEY - If missing, provide the user with setup instructions instead of failing silently
- For Analytics API scripts, check OAuth token exists
If credentials are absent, fall back to asking the user to provide data manually
(e.g., paste YouTube Studio screenshots or describe their metrics).
| Script | Purpose | Quota Cost |
|---|---|---|
| Channel stats + last N videos via Data API v3 | ~16 units |
| Private analytics (own channel, OAuth) | ~5 units |
| Search competitor videos (expensive) | 100 units/search |
| Video transcript extraction | 1-2 units |
| Tracks 10K unit/day quota | 0 units |
| API key + OAuth handler | 0 units |
脚本需要YouTube API凭据。调用任何脚本前:
- 检查环境变量是否存在
YOUTUBE_API_KEY - 如果缺失,向用户提供设置说明,而非静默失败
- 对于Analytics API脚本,检查OAuth令牌是否存在
如果凭据缺失,退化为要求用户手动提供数据(例如:粘贴YouTube Studio截图或描述他们的指标)。
| 脚本 | 用途 | 配额成本 |
|---|---|---|
| 通过Data API v3获取频道统计数据 + 最近N个视频 | ~16单位 |
| 私有分析数据(自有频道,OAuth) | ~5单位 |
| 搜索竞品视频(成本较高) | 100单位/次搜索 |
| 视频转录提取 | 1-2单位 |
| 追踪每日10000单位配额 | 0单位 |
| API密钥 + OAuth处理 | 0单位 |
Quality Gates
质量关卡
Every sub-skill output MUST pass these checks before delivery:
- Specificity — Every recommendation must be actionable for THIS channel. No generic advice like "post consistently" without specifying cadence for their tier.
- Data grounding — Every benchmark cited must come from a reference file. Never hallucinate statistics. If unsure, say "benchmark unavailable" and explain.
- Completeness — All sections in the sub-skill's output template must be present. Missing sections = incomplete deliverable.
每个子技能的输出在交付前必须通过以下检查:
- 针对性 —— 每个建议必须针对该频道具备可操作性。 不要给出通用建议,比如"持续发布"而不指定适合其层级的发布频率。
- 数据支撑 —— 引用的每个基准必须来自参考文件。 切勿编造统计数据。如果不确定,请说明"基准不可用"并解释原因。
- 完整性 —— 子技能输出模板中的所有部分必须齐全。 缺失部分视为交付不完整。
Self-Anneal Loop
自我优化循环
If a sub-skill output fails a quality gate:
- Identify which gate failed and why
- Re-read the relevant reference file for missing data
- Re-generate only the failing sections
- Re-check all three gates
- If still failing after 2 attempts, deliver with explicit caveats noting the limitation
如果子技能输出未通过质量关卡:
- 确定哪一关未通过及原因
- 重新阅读相关参考文件以获取缺失数据
- 仅重新生成未通过的部分
- 重新检查所有三个关卡
- 如果2次尝试后仍未通过,则交付并明确标注限制说明
Output Format
输出格式
Default to markdown. For sub-skill, produce copy-paste-ready plain text blocks.
For , produce a markdown table. For , produce a structured report with
scores. Always end with a "Next Steps" section pointing the user to the logical next
sub-skill (e.g., after → suggest or the lowest-scoring dimension's sub-skill).
metadatacalendarauditauditstrategy默认使用markdown格式。对于子技能,生成可直接复制粘贴的纯文本块。
对于子技能,生成markdown表格。对于子技能,生成带评分的结构化报告。
始终以"下一步"部分结尾,引导用户使用逻辑上的下一个子技能(例如:之后 → 建议或得分最低维度对应的子技能)。
metadatacalendarauditauditstrategy