article-bookmarker
by chliny
Save and organize web articles as bookmarks with AI summaries and auto-tagging. Use when the user wants to bookmark or collect articles.
安装
claude skill add --url github.com/openclaw/skills/tree/main/skills/chliny/article-bookmarker文档
Article Bookmarker Skill
IMPORTANT: Before any operation, read the environment variable
$ARTICLE_BOOKMARK_DIRto determine the bookmark storage directory. All bookmark files and the tag index must be stored under this path. If the variable is not set, prompt the user to configure it.
Quick Start
When the user provides a URL or article text to bookmark:
- Read
$ARTICLE_BOOKMARK_DIRto get the storage path - Use
web_fetchto get the article content - Generate a concise summary using the current model
- Auto-generate relevant tags based on content analysis
- Create a markdown file with URL, content, summary, and tags (see file-structure.md for format details)
- Save to the bookmark directory with descriptive filename
- Update the tag index file
For deletion requests: find the article, confirm details with user, then remove and update index.
Workflow
Adding Articles
1. Read $ARTICLE_BOOKMARK_DIR
2. Receive URL or text content
3. Extract/save content (web_fetch for URLs)
4. Generate summary (model-based)
5. Auto-tag (keyword/topic analysis)
6. Create bookmark file (markdown format)
7. Update tag index
Deleting Articles
1. Read $ARTICLE_BOOKMARK_DIR
2. Identify target article (by filename, topic, or content)
3. Display article details for confirmation
4. Get user confirmation
5. Delete bookmark file
6. Update tag index
Tag Management
Auto-Tagging Logic
Generate tags by analyzing:
- Article domain/topic keywords
- Technical terms and concepts
- Content categories (tutorial, news, research, etc.)
- Named entities and proper nouns
Maintain consistent tag vocabulary to avoid duplicates (e.g., use "AI" not "artificial-intelligence").
Tag Index Format
TAG_INDEX.md maintains bidirectional mapping (see file-structure.md for full format):
# Article Tag Index
## Tags
- **AI**: [article1](article1.md), [article2](article2.md)
- **Research**: [...]
## Articles by Tag Count
- 3 tags: [article1](article1.md)
- 1 tag: [...]
Implementation Details
Content Extraction
- Use
web_fetchwithextractMode: "markdown"for web articles - Handle truncation gracefully (respect
maxCharslimits) - Preserve original formatting where possible
- GitHub Repository URLs: When the URL is a GitHub repository (e.g.,
https://github.com/user/repo), prioritize fetching the README content from the repository's main page or fromREADME.md,readme.md, orREADME.rstfiles in the root directory
Proxy Configuration and Retry
When fetching article content from URLs fails:
- First Attempt: Try fetching without proxy
- On Failure: Load proxy configuration from environment variables:
HTTP_PROXYorhttp_proxy: HTTP proxy URLHTTPS_PROXYorhttps_proxy: HTTPS proxy URLNO_PROXYorno_proxy: Comma-separated list of hosts to bypass
- Retry: Re-attempt fetching with proxy configuration
- Final Failure: Notify user if both attempts fail
Example environment variables:
export HTTP_PROXY="http://proxy.example.com:8080"
export HTTPS_PROXY="http://proxy.example.com:8080"
export NO_PROXY="localhost,127.0.0.1,.example.com"
Summary Generation
Generate 2-3 paragraph summaries that capture:
- Main thesis or argument
- Key insights or findings
- Practical implications or applications
Keep summaries informative but concise (typically 150-300 words).
File Naming
Create SEO-friendly filenames:
- Convert title to lowercase
- Replace spaces and special chars with hyphens
- Limit length to ~50 characters
- Ensure uniqueness by appending numbers if needed
Safety Checks
- Validate URLs before fetching
- Confirm deletions with users (show path and key details)
- Maintain backup of index before modifications
- Handle concurrent access gracefully