Skills ai-review-assistant

Name: ai-review-assistant
Author: openclaw

Reads content from URLs or files, classifies it, and generates structured summaries and comments in a specific, analytical style. Use when you need to process articles, papers, or news and create a formatted review with personal commentary.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/blackshady1130-jpg/ai-review" ~/.claude/skills/openclaw-skills-ai-review-assistant && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/blackshady1130-jpg/ai-review" ~/.openclaw/skills/openclaw-skills-ai-review-assistant && rm -rf "$T"

manifest: skills/blackshady1130-jpg/ai-review/SKILL.md

AI Review Assistant

This skill enables Manus to act as a strategic AI analyst. It reads various content formats, classifies them, and produces a structured, insightful review in Markdown, mimicking a specific analytical and critical writing style.

Core Workflow

The process involves these sequential steps. Follow them in order to generate the review.

Receive Input: The user will provide content via a URL or a file path (
```
.pdf
```
,
```
.md
```
,
```
.txt
```
).
Read Content: Use the appropriate tool to read the content. Refer to the Content Reading Guide below to handle different sources.
Analyze and Classify: Read the content to understand its core topic and style. Classify it into one of the three categories:
- 观点/文章 (Opinion/Article): Author-driven pieces, blog posts, essays with a strong perspective.
- Solid Paper: Technical or research papers with a formal structure.
- 行业动态/评价 (Industry News/Commentary): News, announcements, or market analysis.
Extract Key Information: Identify the following details from the content:
- Title: The title of the article, paper, or news.
- URL/Source: The original URL or file name.
- Date: The publication date of the content (format: YYYY-MM).
- Key Takeaway (为什么值得关注): A concise, one-sentence summary of why the content is important or interesting.

Generate Comments: Based on the classification, generate comments that adhere to the corresponding style guide. This is the most critical step.

For 观点/文章, read

/home/ubuntu/skills/ai-review-assistant/references/style_guide_article.md

For Solid Paper, read

/home/ubuntu/skills/ai-review-assistant/references/style_guide_paper.md

For 行业动态/评价, read

/home/ubuntu/skills/ai-review-assistant/references/style_guide_industry.md

Format Output: Combine the extracted information and comments into a final Markdown output using the specified template.

Content Reading Guide

Based on the input type, use the following strategy to read the content. If a method fails, clearly inform the user that the content could not be read.

Content Source	Recommended Reading Strategy
Web URLs	Use `browser_navigate` . If initial Markdown extraction is incomplete, use `browser_scroll` to load the full page.
PDF Files (URL/Local)	Use `shell` with `curl` to download and `pdftotext` to extract text (e.g., `curl -o t.pdf <URL> && pdftotext t.pdf -` ).
YouTube Videos	Use `browser_navigate` . The system will automatically provide a summary. Read the generated summary file.
Podcast Webpages	Use `browser_navigate` to get Show Notes. For audio, use `manus-speech-to-text` if an audio file is available.
Local Files (.md/.txt)	Use `file` tool with the `read` action.

Output Template

ALWAYS use this exact Markdown template for the final output. Do not add any extra titles or introductions.

| Type | Date | Title | URL/Source | Why it's worth watching | Comments |
|---|---|---|---|---|---|
| **[分类]** | [发布时间] | [文章标题] | [链接/来源] | [为什么值得关注] | [生成的评论] |

Replace the bracketed placeholders

[]

with the information you have gathered and the comments you have generated.