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Fs Street
作者
hjw21century
· GitHub ↗
· v0.1.0
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版本数
在 OpenClaw 中安装
/install fs-street
功能描述
Fetches articles from Farnam Street RSS. Use when asking about decision-making, mental models, learning, or wisdom from Farnam Street blog.
使用说明 (SKILL.md)
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
python skills/fs-street/scripts/fetch_blog.py --date YYYY-MM-DD
Available commands:
# 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
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:
# 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
# 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
安全使用建议
This skill appears coherent and limited to fetching Farnam Street RSS entries. Before installing: (1) note you may need to pip install feedparser and requests if you run the script locally; (2) adjust the script path in the docs if you invoke it exactly as shown (use scripts/fetch_blog.py or update the path to where the agent installs skills); (3) be aware the skill fetches content from fs.blog over the network and may show only teasers for members-only posts; (4) no secrets or broad permissions are requested. If you require stricter controls, run the included script in an isolated environment or inspect it locally before enabling autonomous use.
功能分析
Type: OpenClaw Skill
Name: fs-street
Version: 0.1.0
The OpenClaw skill bundle 'fs-street' is classified as benign. The `SKILL.md` file provides clear, non-malicious instructions for fetching Farnam Street articles and does not contain any prompt injection attempts to subvert the agent's behavior. The `scripts/fetch_blog.py` Python script uses `argparse` for robust command-line argument parsing, hardcodes the RSS feed URL (`https://fs.blog/feed/`), and outputs structured JSON, preventing shell injection or arbitrary code execution within the script itself. There is no evidence of data exfiltration, persistence mechanisms, or other malicious activities.
能力评估
Purpose & Capability
Name and description match the included code and instructions. The only external network access is to the Farnam Street RSS feed (https://fs.blog/feed/), which is exactly what the skill claims to do.
Instruction Scope
SKILL.md instructs running a bundled Python script and includes only feed-related operations and date parsing. One minor inconsistency: the docs show the script path as 'python skills/fs-street/scripts/fetch_blog.py' while the repository file is at 'scripts/fetch_blog.py' — that path mismatch may cause confusion when invoking the CLI exactly as shown.
Install Mechanism
There is no install spec in the registry (instruction-only), and the script depends on public Python packages (feedparser, requests) which the SKILL.md correctly documents (pip install feedparser requests). No downloads from untrusted URLs or archive extraction are present.
Credentials
The skill requires no environment variables, credentials, or config paths. It performs a single, expected network fetch to the public RSS URL; no secrets are requested or used.
Persistence & Privilege
The skill does not request persistent 'always' inclusion and does not modify other skills or system settings. It runs on-demand and prints structured JSON output; autonomous invocation is enabled by platform default but the skill itself has no elevated privileges.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install fs-street - 安装完成后，直接呼叫该 Skill 的名称或使用
/fs-street触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.1.0
- Initial release of the fs-street skill.
- Fetches articles from the Farnam Street blog via RSS.
- Supports queries by absolute and relative dates, date ranges, and topic keywords.
- Provides clear guidance for basic queries and CLI usage.
- Handles premium member-only articles with clear messaging and teasers.
- Includes troubleshooting tips and configuration details.
元数据
常见问题
Fs Street 是什么？
Fetches articles from Farnam Street RSS. Use when asking about decision-making, mental models, learning, or wisdom from Farnam Street blog. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 682 次。
如何安装 Fs Street？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install fs-street」即可一键安装，无需额外配置。
Fs Street 是免费的吗？
是的，Fs Street 完全免费（开源免费），可自由下载、安装和使用。
Fs Street 支持哪些平台？
Fs Street 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Fs Street？
由 hjw21century（@hjw21century）开发并维护，当前版本 v0.1.0。
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