--- name: fs-street description: Fetches articles from Farnam Street RSS. Use when asking about decision-making, mental models, learning, or wisdom from Farnam Street blog. --- # Farnam Street Fetches articles from Farnam Street blog, covering topics like mental models, decision-making, leadership, and learning. ## Quick Start ``` # Basic queries 昨天的文章 今天的FS文章 2024-06-13的文章 # Search 有哪些可用的日期 ``` ## Query Types | Type | Examples | Description | |------|----------|-------------| | Relative date | `昨天的文章` `今天的文章` `前天` | Yesterday, today, day before | | Absolute date | `2024-06-13的文章` | YYYY-MM-DD format | | Date range | `有哪些日期` `可用的日期` | Show available dates | | Topic search | `关于决策的文章` `思维模型` | Search by keyword | ## Workflow ``` - [ ] Step 1: Parse date from user request - [ ] Step 2: Fetch RSS data - [ ] Check content availability - [ ] Format and display results ``` --- ## Step 1: Parse Date | User Input | Target Date | Calculation | |------------|-------------|-------------| | `昨天` | Yesterday | today - 1 day | | `前天` | Day before | today - 2 days | | `今天` | Today | Current date | | `2024-06-13` | 2024-06-13 | Direct parse | **Format**: Always use `YYYY-MM-DD` --- ## Step 2: Fetch RSS ```bash python skills/fs-street/scripts/fetch_blog.py --date YYYY-MM-DD ``` **Available commands**: ```bash # Get specific date python skills/fs-street/scripts/fetch_blog.py --date 2024-06-13 # Get date range python skills/fs-street/scripts/fetch_blog.py --date-range # Relative dates python skills/fs-street/scripts/fetch_blog.py --relative yesterday ``` **Requirements**: `pip install feedparser requests` --- ## Step 3: Check Content ### When NOT Found ```markdown Sorry, no article available for 2024-06-14 Available date range: 2023-04-19 ~ 2024-06-13 Suggestions: - View 2024-06-13 article - View 2024-06-12 article ``` ### Members Only Content Some articles are marked `[FS Members]` - these are premium content and may only show a teaser. --- ## Step 4: Format Results **Example Output**: ```markdown # Farnam Street · 2024年6月13日 > Experts vs. Imitators: How to tell the difference between real expertise and imitation ## Content If you want the highest quality information, you have to speak to the best people. The problem is many people claim to be experts, who really aren't. **Key Insights**: - Imitators can't answer questions at a deeper level - Experts can tell you all the ways they've failed - Imitators don't know the limits of their expertise --- Source: Farnam Street URL: https://fs.blog/experts-vs-imitators/ ``` --- ## Configuration | Variable | Description | Default | |----------|-------------|---------| | RSS_URL | RSS feed URL | `https://fs.blog/feed/` | No API keys required. --- ## Troubleshooting | Issue | Solution | |-------|----------| | RSS fetch fails | Check network connectivity | | Invalid date | Use YYYY-MM-DD format | | No content | Check available date range | | Members only | Some articles are premium content | --- ## CLI Reference ```bash # Get specific date python skills/fs-street/scripts/fetch_blog.py --date 2024-06-13 # Get date range python skills/fs-street/scripts/fetch_blog.py --date-range # Relative dates python skills/fs-street/scripts/fetch_blog.py --relative yesterday ```