blog-analyze

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Original

English

🇨🇳

Translation

Chinese

Blog Analyzer -- Quality Audit & Scoring

博客分析工具 -- 质量审核与评分

Scores blog posts on a 0-100 scale across 5 categories and provides prioritized improvement recommendations. Includes AI content detection analysis. Works with local files or published URLs.

Reference documents:

```
references/quality-scoring.md
```
-- full scoring checklist
```
references/eeat-signals.md
```
-- E-E-A-T evaluation criteria

基于0-100分制对博客文章进行5类别评分，并提供优先级改进建议。包含AI内容检测分析功能，支持本地文件或已发布URL。

参考文档：

```
references/quality-scoring.md
```
-- 完整评分检查表
```
references/eeat-signals.md
```
-- E-E-A-T评估标准

Input Handling

输入处理

Local file: Read the file directly
URL: Fetch with WebFetch, extract content
Directory: Scan for blog files, audit all (batch mode)
Flags:
```
--format json|table
```
,
```
--batch
```
,
```
--sort score
```

本地文件：直接读取文件
URL：通过WebFetch获取并提取内容
目录：扫描博客文件，批量审核所有内容（批量模式）
参数：
```
--format json|table
```
、
```
--batch
```
、
```
--sort score
```

Scoring Process

评分流程

Step 1: Content Extraction

步骤1：内容提取

Read the blog post and extract:

Frontmatter (title, description, date, lastUpdated, author, tags)
Heading structure (H1, H2, H3 with hierarchy)
Paragraph count and word counts per paragraph
Statistics (any number claims with or without sources)
Images (count, alt text presence, format)
Charts/SVGs (count, type diversity)
Links (internal, external, broken)
FAQ section presence
Schema markup (types present)
Meta tags (title, description, OG tags, twitter cards)
Sentence lengths for burstiness analysis
Vocabulary tokens for diversity scoring

读取博客文章并提取以下信息：

Frontmatter（标题、描述、日期、最后更新时间、作者、标签）
标题结构（H1、H2、H3层级）
段落数量及每段字数
统计数据（所有带/不带来源的数值声明）
图片（数量、是否包含替代文本、格式）
图表/SVG（数量、类型多样性）
链接（内部链接、外部链接、失效链接）
是否存在FAQ板块
Schema标记（已有的标记类型）
元标签（标题、描述、OG tags、twitter cards）
句子长度（用于句子长度变化度分析）
词汇标记（用于多样性评分）

Step 2: Score Each Category

步骤2：各类别评分

Load

references/quality-scoring.md

for the full checklist. Score each:

加载

references/quality-scoring.md

获取完整检查表，对每个类别进行评分：

Content Quality (30 points)

内容质量（30分）

Check	Points	Pass Criteria
Depth/comprehensiveness	7	Covers topic thoroughly, no major gaps
Readability (Flesch 60-70)	7	Flesch 60-70 ideal, 55-75 acceptable; Grade 7-8; Gunning Fog 7-8
Originality/unique value markers	5	Original data, case studies, first-hand experience
Sentence & paragraph structure	4	Avg sentence 15-20 words, ≤25% over 20; paragraphs 40-80 words; H2 every 200-300 words
Engagement elements	4	Summary box, callouts, varied content blocks. Accepts: "TL;DR", "Key Takeaways", "The Bottom Line", "What You'll Learn", "At a Glance", "In Brief"
Grammar/anti-pattern	3	Passive voice ≤10%, AI trigger words ≤5/1K, transition words 20-30%, clean prose

Readability Bands (apply per persona, or use default):

Audience	Flesch Grade	Flesch Ease	Scoring Impact
Consumer	6-8	60-80	Full points if in range
Professional	8-10	50-60	Full points if in range
Technical	10-12	30-50	Full points if in range
Default (no persona)	7-8	60-70	Current scoring unchanged

Content clarity is the #2 factor for AI citation probability (+32.83% score differential). Average US adult reads at 7th-8th grade level.

检查项	分值	通过标准
深度/全面性	7	全面覆盖主题，无重大遗漏
可读性（Flesch指数60-70）	7	Flesch指数理想范围60-70，可接受范围55-75；对应7-8年级水平；Gunning Fog指数7-8
原创性/独特价值标识	5	包含原创数据、案例研究、一手经验
句子与段落结构	4	平均句长15-20词，超过20词的句子占比≤25%；段落长度40-80词；每200-300词设置一个H2标题
互动元素	4	包含摘要框、提示框、多样化内容模块。可接受形式："TL;DR"、"关键要点"、"总结"、"你将学到什么"、"概览"、"简介"
语法/反模式	3	被动语态占比≤10%，AI触发词≤5个/1000词，过渡词占比20-30%，行文简洁流畅

可读性区间（可针对不同用户群体调整，或使用默认值）：

受众	Flesch年级水平	Flesch易读度	评分影响
普通消费者	6-8	60-80	处于范围内得满分
专业人士	8-10	50-60	处于范围内得满分
技术人员	10-12	30-50	处于范围内得满分
默认（无指定群体）	7-8	60-70	评分规则不变

内容清晰度是影响AI引用概率的第二大因素（得分差异+32.83%）。美国成年人平均阅读水平为7-8年级。

SEO Optimization (25 points)

SEO优化（25分）

Check	Points	Pass Criteria
Heading hierarchy with keywords	5	H1 -> H2 -> H3, no skips, keyword in 2-3 headings
Title tag (40-60 chars, keyword, power word)	4	Front-loaded keyword, positive sentiment
Keyword placement/density	4	Natural integration, no stuffing, in first 100 words
Internal linking (3-10 contextual)	4	Descriptive anchor text, bidirectional
URL structure	3	Short, keyword-rich, no stop words, lowercase
Meta description (150-160 chars, stat)	3	Fact-dense, includes one statistic
External linking (tier 1-3)	2	3-8 outbound links to authoritative sources

检查项	分值	通过标准
含关键词的标题层级	5	遵循H1→H2→H3层级，无跳级，2-3个标题中包含关键词
标题标签（40-60字符，含关键词、强力词汇）	4	前置关键词，语气积极
关键词布局/密度	4	自然融入，无堆砌，在开头100词内出现
内部链接（3-10个上下文相关链接）	4	锚文本描述性强，双向链接
URL结构	3	简短、含关键词、无停用词、全小写
元描述（150-160字符，含统计数据）	3	信息密集，包含至少一项统计数据
外部链接（1-3级来源）	2	3-8个指向权威来源的出站链接

E-E-A-T Signals (15 points)

E-E-A-T信号（15分）

Check	Points	Pass Criteria
Author attribution (named, with bio)	4	Real name, credentials, not sales pitch
Source citations (tier 1-3, inline)	4	8+ unique stats, zero fabricated
Trust indicators	4	Contact page, about page, editorial policy
Experience signals	3	"When we tested...", original photos/data

When scoring source citations under E-E-A-T, evaluate whether each public statistic carries the FLOW evidence triple: year anchor in prose, inline citation with publisher and title, URL with retrieval date in the source block. Posts that cite tier 1-3 sources but lack retrieval dates score lower on this subcategory than posts that include the full triple. See

skills/blog/references/flow-alignment.md

for the standard.

检查项	分值	通过标准
作者署名（真实姓名+简介）	4	真实姓名、资质证明，非销售话术
来源引用（1-3级来源，内嵌引用）	4	至少8个独特统计数据，无伪造内容
信任标识	4	包含联系页面、关于页面、编辑政策
经验信号	3	包含"我们测试时发现..."、原创照片/数据

在E-E-A-T下评分来源引用时，需评估每个公开统计数据是否符合FLOW证据三重标准：正文中的年份锚点、包含出版商和标题的内嵌引用、来源区块中带有检索日期的URL。引用1-3级来源但缺少检索日期的文章，在该子项的得分低于包含完整三重标准的文章。详见

skills/blog/references/flow-alignment.md

中的标准。

Technical Elements (15 points)

技术元素（15分）

Check	Points	Pass Criteria
Schema markup (3+ types = bonus)	4	BlogPosting + FAQ + Person minimum
Image optimization	3	AVIF/WebP, descriptive alt text, lazy except LCP
Structured data elements	2	Tables, lists, comparison blocks
Page speed signals	2	LCP < 2.5s, no render-blocking JS
Mobile-friendliness	2	Responsive, tap targets 48px+
OG/social meta tags	2	og:title, og:description, og:image, twitter:card

检查项	分值	通过标准
Schema标记（3种及以上类型可获加分）	4	至少包含BlogPosting + FAQ + Person类型
图片优化	3	使用AVIF/WebP格式，包含描述性替代文本，除LCP图片外均启用懒加载
结构化数据元素	2	包含表格、列表、对比模块
页面速度信号	2	LCP < 2.5秒，无阻塞渲染的JS
移动端适配	2	响应式设计，点击目标尺寸≥48px
OG/社交元标签	2	包含og:title、og:description、og:image、twitter:card

AI Citation Readiness (15 points)

AI引用就绪度（15分）

Check	Points	Pass Criteria
Passage-level citability (120-180 words)	4	Self-contained sections with stat + source
Q&A formatted sections	3	60-70% of H2s as questions, FAQ present
Entity clarity	3	Unambiguous topic entity, consistent terminology
Content structure for extraction	3	Answer-first, tables with thead, comparison formats
AI crawler accessibility	2	SSR/SSG, no JS-gated content

检查项	分值	通过标准
段落级可引用性（120-180词）	4	独立完整的段落包含统计数据+来源
Q&A格式板块	3	60-70%的H2为问题形式，存在FAQ板块
实体清晰度	3	主题实体明确，术语一致
便于提取的内容结构	3	先给出答案，表格包含表头，采用对比格式
AI爬虫可访问性	2	使用SSR/SSG，无JS限制内容

Step 3: AI Content Detection

步骤3：AI内容检测

Analyze the post for AI-generated content risk:

Burstiness Score (sentence length variance):

Calculate standard deviation of sentence lengths across the post
Human writing: high variance (short punchy + long complex sentences)
AI writing: low variance (consistently medium-length sentences)
Score: 0-10 scale (10 = very human-like burstiness)

Known AI Phrase Detection -- flag occurrences of these 17 phrases:

"It's important to note"
"In today's digital landscape"
"Delve into"
"Navigating the complexities"
"Let's explore"
"Furthermore"
"In conclusion"
"It is worth mentioning"
"Embark on"
"Cutting-edge"
"Leverage" (as a verb, non-financial context)
"Game-changer"
"Revolutionize"
"Streamline"
"Harness the power"
"Dive deep"
"Unlock the potential"
Em dashes (-) - count all instances, flag as AI writing pattern

Vocabulary Diversity (Type-Token Ratio):

Calculate unique words / total words
Human writing: TTR typically 0.4-0.6 for long-form
AI writing: TTR often below 0.35 (repetitive vocabulary)

AI Content Risk Assessment:

Flag if AI probability > 50% based on combined signals
Provide specific passages that triggered the flag
Recommend humanization: personal anecdotes, varied sentence rhythm, domain jargon

分析文章的AI生成内容风险：

句子长度变化度得分（句子长度方差）：

计算整篇文章的句子长度标准差
人工写作：方差高（短句有力+长句复杂）
AI写作：方差低（句子长度始终中等）
评分：0-10分（10=非常接近人工写作的变化度）

已知AI短语检测 -- 标记以下18种短语的出现：

"It's important to note"
"In today's digital landscape"
"Delve into"
"Navigating the complexities"
"Let's explore"
"Furthermore"
"In conclusion"
"It is worth mentioning"
"Embark on"
"Cutting-edge"
"Leverage"（动词，非金融语境）
"Game-changer"
"Revolutionize"
"Streamline"
"Harness the power"
"Dive deep"
"Unlock the potential"
破折号(-) -- 统计所有实例，标记为AI写作模式

词汇多样性（类型-标记比率，Type-Token Ratio）：

计算唯一词数/总词数
人工写作：长篇内容的TTR通常为0.4-0.6
AI写作：TTR常低于0.35（词汇重复）

AI内容风险评估：

若综合信号显示AI生成概率>50%则标记
提供触发标记的具体段落
建议人工优化：添加个人轶事、调整句子节奏、使用领域术语

Step 4: Determine Rating

步骤4：确定评级

Score	Rating	Action
90-100	Exceptional	Publish as-is, flagship content
80-89	Strong	Minor polish, ready for publication
70-79	Acceptable	Targeted improvements needed
60-69	Below Standard	Significant rework required
< 60	Rewrite	Fundamental issues, start from outline

得分	评级	行动建议
90-100	优秀	直接发布，作为核心内容
80-89	良好	小幅润色，即可发布
70-79	合格	需要针对性改进
60-69	不合格	需要重大修改
< 60	重写	存在根本性问题，从大纲重新开始

Step 5: Generate Report

步骤5：生成报告

Default output format (Markdown):

undefined

默认输出格式（Markdown）：

undefined

Blog Quality Report: [Title]

Score: [X]/100 -- [Rating]

Score Breakdown

Category	Score	Max	Notes
Content Quality	X	30	[1-line summary]
SEO Optimization	X	25	[1-line summary]
E-E-A-T Signals	X	15	[1-line summary]
Technical Elements	X	15	[1-line summary]
AI Citation Readiness	X	15	[1-line summary]
Total	X	100

Category	Score	Max	Notes
Content Quality	X	30	[1-line summary]
SEO Optimization	X	25	[1-line summary]
E-E-A-T Signals	X	15	[1-line summary]
Technical Elements	X	15	[1-line summary]
AI Citation Readiness	X	15	[1-line summary]
Total	X	100

AI Content Risk

Burstiness score: [X]/10 ([human-like / moderate / flat])
AI phrases detected: [N] ([list phrases found])
Vocabulary diversity (TTR): [X] ([high / acceptable / low])
AI probability: [X]% -- [No concern / Review recommended / High risk]
Flagged passages: [quote specific flat or formulaic sections, if any]

Burstiness score: [X]/10 ([human-like / moderate / flat])
AI phrases detected: [N] ([list phrases found])
Vocabulary diversity (TTR): [X] ([high / acceptable / low])
AI probability: [X]% -- [No concern / Review recommended / High risk]
Flagged passages: [quote specific flat or formulaic sections, if any]

Issues Found

Critical (Must Fix)

[Issue with specific location and fix]

[Issue with specific location and fix]

High Priority

[Issue with specific location and fix]

[Issue with specific location and fix]

Medium Priority

[Issue with specific location and fix]

[Issue with specific location and fix]

Low Priority

[Issue with specific location and fix]

[Issue with specific location and fix]

Quick Stats

Word count: [N]
Paragraphs: [N] (X over 150 words)
H2 sections: [N] (X as questions, X with answer-first formatting)
Statistics: [N] sourced / [N] unsourced
Images: [N] (X with alt text, formats: ...)
Charts: [N] (types: ...)
Internal links: [N]
External links: [N] (tier breakdown: ...)
Schema types: [list]
OG/social tags: [present/missing]

Word count: [N]
Paragraphs: [N] (X over 150 words)
H2 sections: [N] (X as questions, X with answer-first formatting)
Statistics: [N] sourced / [N] unsourced
Images: [N] (X with alt text, formats: ...)
Charts: [N] (types: ...)
Internal links: [N]
External links: [N] (tier breakdown: ...)
Schema types: [list]
OG/social tags: [present/missing]

Recommended Actions

[Most impactful fix -- Critical items first]
[Second most impactful]
[Third]

Run

/blog rewrite <file>

to apply these optimizations automatically.

undefined

[Most impactful fix -- Critical items first]
[Second most impactful]
[Third]

Run

/blog rewrite <file>

to apply these optimizations automatically.

undefined

Export Formats

导出格式

Default: Markdown Report

默认：Markdown报告

Standard detailed report as shown above.

如上文所示的标准详细报告。

JSON Export (

--format json

)

JSON导出（

--format json

）

Machine-readable output for integration with CI/CD or dashboards:

json

{
  "file": "post.md",
  "title": "...",
  "score": 78,
  "rating": "Acceptable",
  "categories": {
    "content_quality": { "score": 22, "max": 30 },
    "seo_optimization": { "score": 18, "max": 25 },
    "eeat_signals": { "score": 12, "max": 15 },
    "technical_elements": { "score": 13, "max": 15 },
    "ai_citation_readiness": { "score": 13, "max": 15 }
  },
  "ai_detection": {
    "burstiness": 6.2,
    "ai_phrases_found": ["Furthermore", "Let's explore"],
    "ttr": 0.44,
    "ai_probability": 32
  },
  "issues": {
    "critical": [],
    "high": [],
    "medium": [],
    "low": []
  }
}

机器可读格式，适用于CI/CD或仪表板集成：

json

{
  "file": "post.md",
  "title": "...",
  "score": 78,
  "rating": "Acceptable",
  "categories": {
    "content_quality": { "score": 22, "max": 30 },
    "seo_optimization": { "score": 18, "max": 25 },
    "eeat_signals": { "score": 12, "max": 15 },
    "technical_elements": { "score": 13, "max": 15 },
    "ai_citation_readiness": { "score": 13, "max": 15 }
  },
  "ai_detection": {
    "burstiness": 6.2,
    "ai_phrases_found": ["Furthermore", "Let's explore"],
    "ttr": 0.44,
    "ai_probability": 32
  },
  "issues": {
    "critical": [],
    "high": [],
    "medium": [],
    "low": []
  }
}

Table Export (

--format table

)

表格导出（

--format table

）

Compact summary for quick review:

File            | Score | Rating     | Content | SEO | EEAT | Tech | AI-Ready | AI Risk
post.md         |    78 | Acceptable |   22/30 | 18/25 | 12/15 | 13/15 |    13/15 |    32%

简洁摘要，便于快速查看：

File            | Score | Rating     | Content | SEO | EEAT | Tech | AI-Ready | AI Risk
post.md         |    78 | Acceptable |   22/30 | 18/25 | 12/15 | 13/15 |    13/15 |    32%

Batch Mode

批量模式

When given a directory or

--batch

flag, scan for blog files and produce a summary table. Use

--sort score

to order by score (ascending by default).

undefined

当指定目录或使用

--batch

参数时，扫描博客文件并生成汇总表格。使用

--sort score

按得分排序（默认升序）。

undefined

Blog Audit Summary: [N] Posts Analyzed

File	Score	Rating	Content	SEO	EEAT	Tech	AI-Ready	AI Risk	Top Issue
post-1.md	85	Strong	26/30	20/25	13/15	14/15	12/15	18%	Missing OG tags
post-2.md	42	Rewrite	10/30	8/25	5/15	9/15	10/15	71%	12 fabricated stats
post-3.md	71	Acceptable	20/30	16/25	10/15	12/15	13/15	25%	No answer-first

File	Score	Rating	Content	SEO	EEAT	Tech	AI-Ready	AI Risk	Top Issue
post-1.md	85	Strong	26/30	20/25	13/15	14/15	12/15	18%	Missing OG tags
post-2.md	42	Rewrite	10/30	8/25	5/15	9/15	10/15	71%	12 fabricated stats
post-3.md	71	Acceptable	20/30	16/25	10/15	12/15	13/15	25%	No answer-first

Priority Queue (Lowest Scoring First)

post-2.md (42) -- Full rewrite needed, high AI content risk
post-3.md (71) -- Answer-first formatting + stats needed
post-1.md (85) -- Add OG tags, minor polish

Run

/blog rewrite <file>

on each, starting from lowest score.

undefined

post-2.md (42) -- Full rewrite needed, high AI content risk
post-3.md (71) -- Answer-first formatting + stats needed
post-1.md (85) -- Add OG tags, minor polish

Run

/blog rewrite <file>

on each, starting from lowest score.

undefined

blog-analyze

Original

Translation

Blog Analyzer -- Quality Audit & Scoring

博客分析工具 -- 质量审核与评分

Input Handling

输入处理

Scoring Process

评分流程

Step 1: Content Extraction

步骤1：内容提取

Step 2: Score Each Category

步骤2：各类别评分

Content Quality (30 points)

内容质量（30分）

SEO Optimization (25 points)

SEO优化（25分）

E-E-A-T Signals (15 points)

E-E-A-T信号（15分）

Technical Elements (15 points)

技术元素（15分）

AI Citation Readiness (15 points)

AI引用就绪度（15分）

Step 3: AI Content Detection

步骤3：AI内容检测

Step 4: Determine Rating

步骤4：确定评级

Step 5: Generate Report

步骤5：生成报告

Blog Quality Report: [Title]

Blog Quality Report: [Title]

Score Breakdown

Score Breakdown

AI Content Risk

AI Content Risk

Issues Found

Issues Found

Critical (Must Fix)

Critical (Must Fix)

High Priority

High Priority

Medium Priority

Medium Priority

Low Priority

Low Priority

Quick Stats

Quick Stats

Recommended Actions

Recommended Actions

Export Formats

导出格式

Default: Markdown Report

默认：Markdown报告

JSON Export (--format json)

JSON导出（--format json）

Table Export (--format table)

表格导出（--format table）

Batch Mode

批量模式

Blog Audit Summary: [N] Posts Analyzed

Blog Audit Summary: [N] Posts Analyzed

Priority Queue (Lowest Scoring First)

Priority Queue (Lowest Scoring First)

JSON Export (
`--format json`
)

JSON导出（
`--format json`
）

Table Export (
`--format table`
)

表格导出（
`--format table`
）