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Agent Skill · 待分类

blog-analyze(博客分析)

blog-analyze 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

blog-analyze 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 1,807。

总安装 2,258周安装 97GitHub Stars 619下载 792核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:blog-analyze(博客分析)
来源仓库:https://github.com/agricidaniel/claude-blog
仓库路径:skills/blog-analyze
安装命令:
npx skills add https://github.com/agricidaniel/claude-blog --skill blog-analyze
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/agricidaniel/claude-blog --skill blog-analyze

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于对博客文章进行质量评分与 AI 内容检测,输出 0–100 分多维评估报告。适合内容运营者定期审计站点质量或投稿前自我检查原创程度。支持本地文件或 URL 输入,涵盖 E-E-A-T 信号与改进优先级排序。安装方式:GitHub 仓库,使用 npx skills add 命令添加;无外部依赖纯 Claude 处理。

注意:分数仅供参考,高得分不代表内容正确,低分需人工介入复核。

来源仓库内路径:skills/blog-analyze

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/agricidaniel/claude-blog --skill blog-analyze;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

blog-analyze 怎么安装?

在终端执行 npx skills add https://github.com/agricidaniel/claude-blog --skill blog-analyze。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

blog-analyze 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

blog-analyze 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

blog-analyze 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

blog-analyze 用的人多吗?

公开数据是累计安装 2,258 次,近一周安装 97 次,下载 792 次,GitHub 619 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

blog-analyze 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
blog-analyze

博客分析 · 本页

2,258619需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Blog Analyzer -- Quality Audit & Scoring

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

Input Handling

  • 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

Scoring Process

Step 1: Content Extraction

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

Step 2: Score Each Category

Load references/quality-scoring.md for the full checklist. Score each:

Content Quality (30 points)
CheckPointsPass Criteria
Depth/comprehensiveness7Covers topic thoroughly, no major gaps
Readability (Flesch 60-70)7Flesch 60-70 ideal, 55-75 acceptable; Grade 7-8; Gunning Fog 7-8
Originality/unique value markers5Original data, case studies, first-hand experience
Sentence & paragraph structure4Avg sentence 15-20 words, ≤25% over 20; paragraphs 40-80 words; H2 every 200-300 words
Engagement elements4Summary box, callouts, varied content blocks. Accepts: "TL;DR", "Key Takeaways", "The Bottom Line", "What You'll Learn", "At a Glance", "In Brief"
Grammar/anti-pattern3Passive voice ≤10%, AI trigger words ≤5/1K, transition words 20-30%, clean prose

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

AudienceFlesch GradeFlesch EaseScoring Impact
Consumer6-860-80Full points if in range
Professional8-1050-60Full points if in range
Technical10-1230-50Full points if in range
Default (no persona)7-860-70Current 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.

SEO Optimization (25 points)
CheckPointsPass Criteria
Heading hierarchy with keywords5H1 -> H2 -> H3, no skips, keyword in 2-3 headings
Title tag (40-60 chars, keyword, power word)4Front-loaded keyword, positive sentiment
Keyword placement/density4Natural integration, no stuffing, in first 100 words
Internal linking (3-10 contextual)4Descriptive anchor text, bidirectional
URL structure3Short, keyword-rich, no stop words, lowercase
Meta description (150-160 chars, stat)3Fact-dense, includes one statistic
External linking (tier 1-3)23-8 outbound links to authoritative sources
E-E-A-T Signals (15 points)
CheckPointsPass Criteria
Author attribution (named, with bio)4Real name, credentials, not sales pitch
Source citations (tier 1-3, inline)48+ unique stats, zero fabricated
Trust indicators4Contact page, about page, editorial policy
Experience signals3"When we tested...", original photos/data
Technical Elements (15 points)
CheckPointsPass Criteria
Schema markup (3+ types = bonus)4BlogPosting + FAQ + Person minimum
Image optimization3AVIF/WebP, descriptive alt text, lazy except LCP
Structured data elements2Tables, lists, comparison blocks
Page speed signals2LCP < 2.5s, no render-blocking JS
Mobile-friendliness2Responsive, tap targets 48px+
OG/social meta tags2og:title, og:description, og:image, twitter:card
AI Citation Readiness (15 points)
CheckPointsPass Criteria
Passage-level citability (120-180 words)4Self-contained sections with stat + source
Q&A formatted sections360-70% of H2s as questions, FAQ present
Entity clarity3Unambiguous topic entity, consistent terminology
Content structure for extraction3Answer-first, tables with thead, comparison formats
AI crawler accessibility2SSR/SSG, no JS-gated content

Step 3: AI Content Detection

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:

  1. "It's important to note"
  2. "In today's digital landscape"
  3. "Delve into"
  4. "Navigating the complexities"
  5. "Let's explore"
  6. "Furthermore"
  7. "In conclusion"
  8. "It is worth mentioning"
  9. "Embark on"
  10. "Cutting-edge"
  11. "Leverage" (as a verb, non-financial context)
  12. "Game-changer"
  13. "Revolutionize"
  14. "Streamline"
  15. "Harness the power"
  16. "Dive deep"
  17. "Unlock the potential"
  18. 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

Step 4: Determine Rating

ScoreRatingAction
90-100ExceptionalPublish as-is, flagship content
80-89StrongMinor polish, ready for publication
70-79AcceptableTargeted improvements needed
60-69Below StandardSignificant rework required
< 60RewriteFundamental issues, start from outline

Step 5: Generate Report

Default output format (Markdown):

## 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** | |

### 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]

### Issues Found

#### Critical (Must Fix)
- [ ] [Issue with specific location and fix]

#### High Priority
- [ ] [Issue with specific location and fix]

#### Medium Priority
- [ ] [Issue with specific location and fix]

#### Low Priority
- [ ] [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]

### Recommended Actions
1. [Most impactful fix -- Critical items first]
2. [Second most impactful]
3. [Third]

Run `/blog rewrite <file>` to apply these optimizations automatically.

Export Formats

Default: Markdown Report

Standard detailed report as shown above.

JSON Export (--format json)

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

{
  "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)

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%

Batch Mode

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).

## 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 |

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

Run `/blog rewrite <file>` on each, starting from lowest score.

平台分布

Codex

36.57%
按下载量换算290

Claude

30%
按下载量换算238

Cursor

17.45%
按下载量换算138

Gemini CLI

9.3%
按下载量换算74

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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