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yanpeipan

Feedship

作者 Yan Zer0 · GitHub ↗ · v1.5.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install feedship
功能描述
Manage RSS/Atom feeds, subscribe to websites, search and read articles. Use when working with feeds, RSS, Atom, subscribing to content sources, managing an i...
使用说明 (SKILL.md)

Feedship Skill

Version: 1.5 For: Claude Code and OpenClaw compatible agents Description: Manage information feeds, subscribe to RSS/GitHub sources, and search articles

Setup

Before using this skill, install feedship with ML and cloud extras:

uv tool install 'feedship[ml,cloudflare]' --python 3.12 --force

Note: cloudflare extra provides scrapling (HTML fetching); ml extra provides sentence-transformers + chromadb (semantic search). Both are required for full functionality.

China / Restricted Networks

For environments where PyPI or HuggingFace is not accessible, use mirrors:

# Add to ~/.bashrc for persistence
echo 'export HF_ENDPOINT=https://hf-mirror.com' >> ~/.bashrc
echo 'export PIP_INDEX_URL=https://mirrors.aliyun.com/pypi/simple/' >> ~/.bashrc
source ~/.bashrc

# Install
uv tool install 'feedship[cloudflare,ml]' --force

Upgrade

# From PyPI (if accessible)
uv tool upgrade feedship

# From GitHub (latest commits)
uv tool install 'feedship @ git+https://github.com/yanpeipan/feedship.git' \
  --pip-args='-i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com' \
  --include-deps --force

After installation, verify with: feedship --version

First-time setup for semantic search: After installing, run feedship fetch --all to populate the vector database with article embeddings. Semantic search requires embeddings to be generated first (chromadb storage).

Commands

feed

Manage RSS/Atom feeds and GitHub release trackers.

feed add

feedship feed add \x3Curl> [options]

Add a new feed by URL with automatic provider detection.

Options:

  • --auto-discover/--no-auto-discover — Enable feed auto-discovery (default: enabled)
  • --automatic on|off — Automatically add all discovered feeds (default: off)
  • --discover-depth N — Discovery crawl depth 1-10 (default: 1)
  • --weight FLOAT — Feed weight for semantic search (default: 0.3)

Examples:

feedship feed add https://example.com
feedship feed add https://github.com/python/cpython --automatic on
feedship feed add https://example.com --discover-depth 3

feed list

feedship feed list [-v]

List all subscribed feeds with status.

Options:

  • -v, --verbose — Show detailed output
  • --json — Output in JSON format for programmatic consumption

feed remove

feedship feed remove \x3Cfeed-id>

Remove a subscribed feed by ID.

fetch

feedship fetch [--all|\x3Cfeed-ids>] [--concurrency N]

Fetch new articles from subscribed feeds.

Options:

  • --all — Fetch all subscribed feeds
  • --concurrency N — Max concurrent fetches 1-100 (default: 10)

Examples:

feedship fetch --all
feedship fetch abc12345
feedship fetch abc12345 def67890 --concurrency 20

article

Manage and view fetched articles.

article list

feedship article list [options]

Options:

  • --limit N — Maximum articles (default: 20)
  • --feed-id \x3Cid> — Filter by feed ID
  • --since \x3Cdate> — Start date (YYYY-MM-DD)
  • --until \x3Cdate> — End date (YYYY-MM-DD)
  • --on \x3Cdate> — Specific date (can repeat for multiple)
  • --json — Output in JSON format for programmatic consumption

article view

feedship article view \x3Carticle-id>

View full article content and metadata.

article open

feedship article open \x3Carticle-id>

Open article in system browser.

article related

feedship article related \x3Carticle-id> [--limit N]

Find semantically related articles.

search

feedship search \x3Cquery> [options]

Search articles using full-text or semantic search.

Options:

  • --limit N — Maximum results (default: 20)
  • --feed-id \x3Cid> — Filter by feed ID
  • --semantic — Use semantic (vector) search instead of keyword
  • --rerank — Apply Cross-Encoder reranking
  • --since \x3Cdate> — Start date filter
  • --until \x3Cdate> — End date filter
  • --on \x3Cdate> — Specific date filter
  • --json — Output in JSON format for programmatic consumption

Examples:

feedship search "machine learning"
feedship search "python news" --semantic
feedship search "updates" --semantic --rerank

discover

feedship discover \x3Curl> [--discover-depth N]

Discover RSS/Atom/RDF feeds on a website without subscribing.

Options:

  • --discover-depth N — Crawl depth 1-10 (default: 1)
  • --json — Output in JSON format for programmatic consumption

Examples:

feedship discover example.com
feedship discover example.com --discover-depth 3

info

feedship info [options]

Display system information, configuration, and storage status.

Options:

  • --json — Output in JSON format for programmatic consumption

Output includes:

  • Version information
  • Configuration file location
  • Database/storage path
  • Feed count and article count
  • Installed extras (ml, cloudflare)

Examples:

feedship info
feedship info --json

Output Formats

Tables

feed list, article list, search, discover output Rich tables:

  • Magenta headers
  • Alternating row styles
  • Truncated columns with overflow indicators

Panels

article view uses Rich Panel:

  • Title: Article title
  • Subtitle: Feed name | Date
  • Content: Full article text

Progress Bars

fetch uses Rich progress bars showing:

  • Current feed being fetched
  • New articles count
  • Elapsed time

Common Patterns

Initial Setup

# Add a website feed
feedship feed add https://example.com --automatic on

# Fetch all feeds
feedship fetch --all

# View recent articles
feedship article list --limit 50

Daily Workflow

# Fetch new articles
feedship fetch --all

# Search for topics
feedship search "machine learning" --semantic

# Read an article
feedship article view abc12345

# Open in browser for full view
feedship article open abc12345

Feed Management

# List feeds
feedship feed list -v

# Remove stale feed
feedship feed remove old123

# Discover new feeds on site
feedship discover news-site.com --discover-depth 2

Scheduled Fetching (OpenClaw Best Practice)

For automated periodic fetching, use platform-specific schedulers:

macOS (LaunchAgent):

\x3C!-- ~/Library/LaunchAgents/com.feedship.fetch.plist -->
\x3Ckey>ProgramArguments\x3C/key>\x3Carray>\x3Cstring>/usr/local/bin/feedship\x3C/string>\x3Cstring>fetch\x3C/string>\x3Cstring>--all\x3C/string>\x3C/array>
\x3Ckey>StartInterval\x3C/key>\x3Cinteger>3600\x3C/integer>  \x3C!-- every hour -->

Linux (systemd timer):

# ~/.config/systemd/user/feedship.timer
[Timer] OnBootSec=5min OnUnitActiveSec=1h

Cron:

0 * * * * feedship fetch --all >> ~/.feedship/fetch.log 2>&1

OpenClaw Cron (every 30 minutes):

openclaw cron add \
  --name "feedship-fetch" \
  --agent agent \
  --cron "*/30 * * * *" \
  --tz Asia/Shanghai \
  --session isolated \
  --message "uv run --with feedship[ml,cloudflare] feedship fetch --all" \
  --timeout-seconds 1800

Optional Dependencies

ML Extra (pip install feedship[ml])

Required for semantic search and related articles:

  • sentence-transformers
  • chromadb
  • torch

Cloudflare Extra (pip install feedship[cloudflare])

For enhanced web scraping with:

  • browserforge
  • playwright
  • curl-cffi
安全使用建议
This skill appears to be what it says: a feed manager with optional semantic search. Before installing: 1) Verify the 'uv' CLI referenced is the tool you expect and is trusted on your system. 2) Inspect the feedship package source (PyPI page or the GitHub repo) before running install, especially if using the git+https install. 3) Be aware the 'ml' extras will pull large ML libraries (sentence-transformers, chromadb) — they will consume disk space and may download models. 4) Exercise caution when following the mirror instructions: only set HF_ENDPOINT or PIP_INDEX_URL to mirrors you trust (a malicious mirror can serve poisoned packages or model files). 5) Note that running the tool and the cron behavior will create local databases (article storage and embeddings) and schedule periodic network fetches; if you want no persistence, avoid adding exports to ~/.bashrc and review what feedship stores (config/db paths reported by feedship info). If you need higher assurance, ask the publisher for an official homepage or signed releases, or audit the repository before installing.
功能分析
Type: OpenClaw Skill Name: feedship Version: 1.5.0 The skill instructions in SKILL.md direct the agent to modify the user's shell configuration (~/.bashrc) to persistently redirect PyPI and HuggingFace traffic to third-party mirrors (e.g., mirrors.aliyun.com and hf-mirror.com). While these actions are framed as support for restricted networks, modifying shell startup files and altering package manager sources are high-risk behaviors that create persistence and introduce supply chain vulnerabilities. Additionally, the setup encourages installing the tool directly from a specific GitHub repository (github.com/yanpeipan/feedship.git) rather than a verified registry.
能力评估
✓ Purpose & Capability
Name/description (RSS/Atom, discovery, semantic search) matches the instructions: installing feedship with 'ml' and 'cloudflare' extras, fetching feeds, and building embeddings is coherent. The declared required binary 'uv' is consistent with the provided install commands (uv tool install).
ℹ Instruction Scope
SKILL.md stays within feed-management scope: it instructs installing the tool, fetching feeds, discovery, and running searches. It does suggest persistent changes (adding exports to ~/.bashrc) and running feedship fetch --all to populate local vector DB; these are reasonable for the described functionality but are actions that modify user environment and create local storage.
ℹ Install Mechanism
There is no built-in install spec in the skill; instructions tell the user to run 'uv tool install' pulling from PyPI or a GitHub repo. Using PyPI/GitHub is expected, but the install will pull heavy ML dependencies (sentence-transformers, chromadb) and a scraping extra; those are proportionate but increase attack surface. The GitHub URL shown is a direct repo install (typical but worth verifying).
ℹ Credentials
No required credentials are declared. The doc suggests optionally setting HF_ENDPOINT and PIP_INDEX_URL for mirrors; these are plausible for environments with restricted network access but could redirect package and model downloads to arbitrary endpoints if misconfigured. The skill does not request unrelated secrets.
ℹ Persistence & Privilege
always:false (no forced inclusion). Metadata includes a cron default to fetch every 30 minutes, which is coherent for a feed fetcher. The instructions also propose adding exports to ~/.bashrc (user-level persistence). These behaviors create ongoing network activity and local data (database/vector store) but do not request elevated system privileges.
如何使用
  1. 确保已安装 OpenClaw（本地或 Docker 部署）
  2. 在对话框中输入安装命令：/install feedship
  3. 安装完成后，直接呼叫该 Skill 的名称或使用 /feedship 触发
  4. 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
v1.5.0
feedship 1.5.0 - Added info command to display system configuration, storage, and version info. - New --json output option for feed list, article list, search, discover, and info commands. - OpenClaw cron integration: default scheduled article fetching every 30 minutes. - Setup instructions now favor uv tool installation; pipx instruction removed. - Documentation improvements for automation and scheduler usage (macOS, Linux, Cron, OpenClaw). - Various options clarified in command descriptions and usage examples.
v1.2.2
- Added guidance for using PyPI and HuggingFace mirrors (Aliyun, hf-mirror) in restricted networks. - Updated setup instructions to include persistent environment variable export for both HF_ENDPOINT and PIP_INDEX_URL. - Added upgrade instructions, including options for upgrading directly from GitHub. - No changes to commands or usage; documentation improvements only.
v1.2.1
- Installation instructions updated: pipx with extras ([cloudflare,ml]) is now the recommended method, with uv as an alternative. - Added notes about the purpose and requirement of the [cloudflare] and [ml] extras for full functionality. - Included HuggingFace mirror setup guidance for restricted networks. - Clarified first-time semantic search setup requirements in the documentation. - No command or functionality changes; documentation improvements only.
v1.0.0
Feedship 1.0.0 — Initial Release - Manage RSS/Atom feeds: add, list, remove subscriptions. - Fetch articles from subscribed feeds and manage or view article content. - Search articles using full-text or semantic (vector) search. - Discover feeds on websites without subscribing. - Outputs presented as Rich tables, panels, and progress bars for enhanced UX. - Optional ML and Cloudflare extras for semantic features and advanced scraping.
元数据
Slug feedship
版本 1.5.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 4
常见问题

Feedship 是什么？

Manage RSS/Atom feeds, subscribe to websites, search and read articles. Use when working with feeds, RSS, Atom, subscribing to content sources, managing an i... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 139 次。

如何安装 Feedship？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install feedship」即可一键安装，无需额外配置。

Feedship 是免费的吗？

是的，Feedship 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Feedship 支持哪些平台？

Feedship 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 Feedship？

由 Yan Zer0（@yanpeipan）开发并维护，当前版本 v1.5.0。

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