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Awesome AI Sources

作者 sunxiayi · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-news-fetcher
功能描述
Fetch curated AI news, social signals, blogs, papers, events, and skills from the Agentic Brew public RSS feeds (https://www.agenticbrew.ai/feed/*.xml) and r...
使用说明 (SKILL.md)

Agentic Brew Feed Fetcher

Pulls items from the Agentic Brew public RSS endpoints and returns them as a clean list. No auth, no scraping — just an HTTP GET against the latest run_log's published feed.

Available feeds

Feed URL Contents Item \x3Clink> resolves to
news https://www.agenticbrew.ai/feed/news.xml Synthesized news clusters — title + overview Agentic Brew news-analysis card page (https://www.agenticbrew.ai/news#cluster=\x3Cid>)
twitter https://www.agenticbrew.ai/feed/twitter.xml Trending X / Twitter topics — title + hottest tweets with likes / RTs / replies / views The top tweet of the topic on x.com
github https://www.agenticbrew.ai/feed/github.xml Trending GitHub AI repos — title + detail (stars, language, daily delta) Original GitHub repo
reddit https://www.agenticbrew.ai/feed/reddit.xml Trending Reddit AI threads — title + detail (subreddit, upvotes, comments, excerpt) Original Reddit thread
youtube https://www.agenticbrew.ai/feed/youtube.xml Curated AI videos — title + summary Original YouTube video
product_hunt https://www.agenticbrew.ai/feed/product_hunt.xml Trending AI launches — title + topics + tagline Original Product Hunt launch page
skill https://www.agenticbrew.ai/feed/skill.xml Top Claude Code skills from skills.sh + clawhub — title + installs/stars + summary Original skill page on skills.sh / clawhub
blog https://www.agenticbrew.ai/feed/blog.xml Curated AI blog articles — title + AI-generated summary Original blog article
paper https://www.agenticbrew.ai/feed/paper.xml Research papers — title + AI summary + institutions + source (HF/AlphaXiv/X) + votes Original paper page (arxiv / Hugging Face / x.com)
event https://www.agenticbrew.ai/feed/event.xml Upcoming AI events — title + start time + summary Original event page (e.g., lu.ma)
all https://www.agenticbrew.ai/feed/all.xml Union of all of the above Per-item — same as the feed above

Usage

/ai-news-radar [feed] [--limit N] [--query KEYWORD] [--json]
  • feed (optional, default news): one of news, twitter, github, reddit, youtube, product_hunt, skill, blog, paper, event, all
  • --limit N (optional, default 20): max items to return
  • --query KEYWORD (optional): case-insensitive substring filter over title + description
  • --json (optional): emit JSON instead of markdown

Default interactive flow (no args, or vague request)

This skill covers a lot of ground — 11 feeds spanning news, social, papers, events, and more. If the user invokes it without specifying a feed (e.g., "show me what's new on Agentic Brew", "give me today's AI digest"), do NOT silently default to one feed. Instead, before fetching anything:

  1. Ask the user which categories they want. Use the host agent's question UI (in Claude Code: AskUserQuestion with multiSelect: true) so the user can pick any subset of:

    news, twitter, github, reddit, youtube, product_hunt, skill, blog, paper, event

    Plus an all shortcut. Show a one-line description of each so the user knows what they're picking. If the user says "everything" or "all", treat as all.

  2. Ask the delivery frequency. Single-select:

    • once — fetch immediately and return the result.
    • daily — fetch now AND propose setting up a recurring task. In Claude Code, suggest the /schedule skill (cron) or /loop (interval). For other host agents, surface their equivalent or tell the user how to re-invoke.
    • weekly — same idea, weekly cadence.
  3. Ask how much detail to include per item. Single-select:

    • headlines — title only. Compact list, just "what happened."
    • summary — title + the AI-generated summary / overview / engagement stats (whichever the feed provides) + the source link. The default Agentic Brew item shape.
    • detailed — title + full description (no truncation) + source link + any content:encoded inner content (e.g., tweet list for twitter, overview bullets for news) + the \x3Ccategory> tags.

    To apply the choice: fetch with --json internally, then format the items per the chosen detail level. Do NOT pass --limit so low that you lose information the user asked for — only --limit controls how many items, not how deep each one goes.

  4. Once the user has answered all three, fetch the selected feeds in parallel and present a single combined report grouped by category, formatted at the chosen detail level. If they chose daily/weekly, ALSO offer to set up the recurring schedule before exiting — don't silently leave it as a one-shot.

If the user provides explicit args (e.g., /ai-news-radar news --limit 5), skip the questions entirely and execute directly per the Usage section.

Steps (direct invocation)

  1. Resolve the feed URL from the chosen feed name. If the argument is invalid, abort and tell the user the valid options.
  2. Run the fetch + parse one-liner below. It uses the Python stdlib only (urllib, xml.etree) — no extra installs.
  3. Print the result. Default output is a markdown list (- [title](link) — pubDate · description). With --json, print a JSON array of {title, link, description, pub_date, categories}.

Fetch + parse one-liner

Substitute FEED, LIMIT, QUERY, and FORMAT (md or json) before running.

FEED="news"      # news | twitter | github | reddit | youtube | product_hunt | skill | blog | paper | event | all
LIMIT=20
QUERY=""         # empty = no filter
FORMAT="md"      # md | json

python3 - "$FEED" "$LIMIT" "$QUERY" "$FORMAT" \x3C\x3C'PY'
import json, sys, urllib.request, xml.etree.ElementTree as ET

FEED, LIMIT, QUERY, FORMAT = sys.argv[1], int(sys.argv[2]), sys.argv[3].lower(), sys.argv[4]
URL = f"https://www.agenticbrew.ai/feed/{FEED}.xml"

req = urllib.request.Request(URL, headers={"User-Agent": "ai-news-radar-skill/1.0"})
with urllib.request.urlopen(req, timeout=30) as r:
    xml_bytes = r.read()

root = ET.fromstring(xml_bytes)
items = []
for it in root.iter("item"):
    def text(tag):
        el = it.find(tag)
        return (el.text or "").strip() if el is not None and el.text else ""
    title = text("title")
    link = text("link")
    desc = text("description")
    pub = text("pubDate")
    cats = [c.text.strip() for c in it.findall("category") if c.text]
    hay = f"{title}\
{desc}".lower()
    if QUERY and QUERY not in hay:
        continue
    items.append({
        "title": title, "link": link, "description": desc,
        "pub_date": pub, "categories": cats,
    })
    if len(items) >= LIMIT:
        break

if FORMAT == "json":
    print(json.dumps(items, ensure_ascii=False, indent=2))
else:
    for i in items:
        d = i["description"]
        if len(d) > 200: d = d[:199] + "…"
        print(f"- [{i['title']}]({i['link']}) — {i['pub_date']}\
  {d}")
    if not items:
        print("(no items matched)")
PY

Notes

  • The feeds always reflect the latest published run_log, so calling this skill twice in the same day usually returns the same items. There is no incremental cursor — caller is responsible for dedup if needed.
  • On non-2xx HTTP responses, surface the status code and URL in RED so the user can see which endpoint failed.
  • If xml.etree cannot parse the body, log a YELLOW warning with the first 200 chars of the response so the user can diagnose (likely a CDN error page, not XML).
  • This skill is read-only against a public endpoint — no credentials, no rate limiting on the caller side. Be polite: do not call in a tight loop.
安全使用建议
This skill looks reasonable for fetching public AI RSS feeds. Before installing, be aware that it will make outbound requests to www.agenticbrew.ai, may run a local Python fetch/parse command, and can propose recurring schedules if you choose daily or weekly delivery.
功能分析
Type: OpenClaw Skill Name: ai-news-fetcher Version: 1.0.0 The skill is a straightforward RSS feed fetcher for AI news from agenticbrew.ai. It uses a standard Python script (via urllib and xml.etree) to parse public feeds and provides an interactive flow for the agent to query user preferences. No malicious indicators, data exfiltration, or suspicious execution patterns were identified.
能力评估
Purpose & Capability
The stated purpose and instructions consistently focus on fetching public Agentic Brew RSS feeds and returning markdown or JSON lists; the provided artifacts do not show credential use, file writes, account mutation, or unrelated behavior.
Instruction Scope
The skill can fetch multiple public feed categories and produce detailed content from RSS items, but it also instructs the agent to ask the user before ambiguous broad fetches.
Install Mechanism
There is no install spec and no code file, but SKILL.md references an inline Python standard-library fetch/parse command; the provided SKILL.md excerpt is truncated before the full command.
Credentials
Outbound HTTPS to enumerated public RSS URLs is proportionate to the skill's feed-reading purpose, and no sensitive local data access is shown.
Persistence & Privilege
Daily or weekly modes propose using scheduling/loop functionality, but the instructions frame this as something to offer the user rather than silently enabling.
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 ai-news-fetcher
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-news-fetcher 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
v1.0.0
- Now fetches curated AI news, social signals, blogs, papers, events, and skills from Agentic Brew public RSS feeds. - Added support for 11 feeds spanning news, social platforms (Twitter, Reddit, YouTube, Product Hunt, GitHub), blogs, papers, events, and top AI skills. - Provides an interactive flow for vague requests: guides users to choose categories, delivery frequency (once, daily, weekly), and preferred detail level (headline, summary, detailed). - Direct command usage allows specifying feed, result limit, keyword filter, and output format (markdown or JSON). - Uses efficient, no-auth RSS fetching—no scraping required.
元数据
Slug ai-news-fetcher
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Awesome AI Sources 是什么?

Fetch curated AI news, social signals, blogs, papers, events, and skills from the Agentic Brew public RSS feeds (https://www.agenticbrew.ai/feed/*.xml) and r... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 93 次。

如何安装 Awesome AI Sources?

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

Awesome AI Sources 是免费的吗?

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

Awesome AI Sources 支持哪些平台?

Awesome AI Sources 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 Awesome AI Sources?

由 sunxiayi(@sunxiayi)开发并维护,当前版本 v1.0.0。

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