功能描述

Comprehensive news aggregator that fetches, filters, and deeply analyzes real-time content from 28 sources including Hacker News, GitHub, Hugging Face Papers...

使用说明 (SKILL.md)

News Aggregator Skill

Name: News Aggregator Skill
Author: abigale-cyber

Fetch real-time hot news from 28 sources, generate deep analysis reports in Chinese.

🔄 Universal Workflow (3 Steps)

Every news request follows the same workflow, regardless of source or combination:

Step 1: Fetch Data

# Single source
python3 scripts/fetch_news.py --source \x3Csource_key> --no-save

# Multiple sources (comma-separated)
python3 scripts/fetch_news.py --source hackernews,github,wallstreetcn --no-save

# All sources (broad scan)
python3 scripts/fetch_news.py --source all --limit 15 --deep --no-save

# With keyword filter (auto-expand: "AI" → "AI,LLM,GPT,Claude,Agent,RAG")
python3 scripts/fetch_news.py --source hackernews --keyword "AI,LLM,GPT" --deep --no-save

Step 2: Generate Report

Read the output JSON and format every item using the Unified Report Template below. Translate all content to Simplified Chinese.

Step 3: Save & Present

Save the report to reports/YYYY-MM-DD/\x3Csource>_report.md, then display the full content to the user.

📰 Unified Report Template

All sources use this single template. Show/hide optional fields based on data availability.

#### N. [标题 (中文翻译)](https://original-url.com)
- **Source**: 源名 | **Time**: 时间 | **Heat**: 🔥 热度值
- **Links**: [Discussion](hn_url) | [GitHub](gh_url)     ← 仅在数据存在时显示
- **Summary**: 一句话中文摘要。
- **Deep Dive**: 💡 **Insight**: 深度分析（背景、影响、技术价值）。

Source-Specific Adaptations

Only the differences from the universal template:

Source	Adaptation
Hacker News	MUST include `[Discussion](hn_url)` link
GitHub	Use `🌟 Stars` for Heat, add `Lang` field, add `#Tags` in Deep Dive
Hugging Face	Use `🔥 +N` upvotes for Heat, include `[GitHub](url)` if present, write 深度解读 (not just translate abstract)
Weibo	Preserve exact heat text (e.g. "108万")

🛠️ Tools

fetch_news.py

Arg	Description	Default
`--source`	Source key(s), comma-separated. See table below.	`all`
`--limit`	Max items per source	`15`
`--keyword`	Comma-separated keyword filter	None
`--deep`	Download article text for richer analysis	Off
`--save`	Force save to reports dir	Auto for single source
`--outdir`	Custom output directory	`reports/YYYY-MM-DD/`

Available Sources (28)

Category	Key	Name
Global News	`hackernews`	Hacker News
	`36kr`	36氪
	`wallstreetcn`	华尔街见闻
	`tencent`	腾讯新闻
	`weibo`	微博热搜
	`v2ex`	V2EX
	`producthunt`	Product Hunt
	`github`	GitHub Trending
AI/Tech	`huggingface`	HF Daily Papers
	`ai_newsletters`	All AI Newsletters (aggregate)
	`bensbites`	Ben's Bites
	`interconnects`	Interconnects (Nathan Lambert)
	`oneusefulthing`	One Useful Thing (Ethan Mollick)
	`chinai`	ChinAI (Jeffrey Ding)
	`memia`	Memia
	`aitoroi`	AI to ROI
	`kdnuggets`	KDnuggets
Podcasts	`podcasts`	All Podcasts (aggregate)
	`lexfridman`	Lex Fridman
	`80000hours`	80,000 Hours
	`latentspace`	Latent Space
Essays	`essays`	All Essays (aggregate)
	`paulgraham`	Paul Graham
	`waitbutwhy`	Wait But Why
	`jamesclear`	James Clear
	`farnamstreet`	Farnam Street
	`scottyoung`	Scott Young
	`dankoe`	Dan Koe

daily_briefing.py (Morning Routines)

Pre-configured multi-source profiles:

python3 scripts/daily_briefing.py --profile \x3Cprofile>

Profile	Sources	Instruction File
`general`	HN, 36Kr, GitHub, Weibo, PH, WallStreetCN	`instructions/briefing_general.md`
`finance`	WallStreetCN, 36Kr, Tencent	`instructions/briefing_finance.md`
`tech`	GitHub, HN, Product Hunt	`instructions/briefing_tech.md`
`social`	Weibo, V2EX, Tencent	`instructions/briefing_social.md`
`ai_daily`	HF Papers, AI Newsletters	`instructions/briefing_ai_daily.md`
`reading_list`	Essays, Podcasts	(Use universal template)

Workflow: Execute script → Read corresponding instruction file → Generate report following both the instruction file AND the universal template.

⚠️ Rules (Strict)

Language: ALL output in Simplified Chinese (简体中文). Keep well-known English proper nouns (ChatGPT, Python, etc.).
Time: MANDATORY field. Never skip. If missing in JSON, mark as "Unknown Time". Preserve "Real-time" / "Today" / "Hot" as-is.
Anti-Hallucination: Only use data from the JSON. Never invent news items. Use simple SVO sentences. Do not fabricate causal relationships.
Smart Keyword Expansion: When user says "AI" → auto-expand to "AI,LLM,GPT,Claude,Agent,RAG,DeepSeek". Similar expansions for other domains.
Smart Fill: If results \x3C 5 items in a time window, supplement with high-value items from wider range. Mark supplementary items with ⚠️.
Save: Always save report to reports/YYYY-MM-DD/ before displaying.

📋 Interactive Menu

When the user says "如意如意" or asks for "menu/help":

Read templates.md
Display the menu
Execute the user's selection using the Universal Workflow above

Requirements

Python 3.8+, pip install -r requirements.txt
Playwright (for HF Papers & Ben's Bites): playwright install chromium

安全使用建议

This skill appears to implement what it claims (web scraping + Playwright-based deep fetch + markdown reports) but has several worrying inconsistencies and operational risks. Before installing or enabling it: - Do NOT grant system-level scheduling (crontab) or run suggested cron commands without manual review; the implementation_plan proposes this but it is not present as an installed artifact. Scheduling would allow persistent, autonomous network access. - Treat the SKILL.md as potentially adversarial: remove or inspect any invisible Unicode control characters and any 'magic phrase' triggers (the skill listens for the phrase “如意如意”). - Install and run in a sandboxed environment first (container or VM). Verify dependencies (pip packages and Playwright + Chromium) are installed explicitly; the registry lacks a formal install spec even though scripts need these runtimes. - Audit scripts that launch Playwright and write files (reports/YYYY-MM-DD/) — check file paths and ensure the skill cannot read unrelated user files. MISTAKES.md shows the author previously read files outside the expected path, so confirm the runtime does not search or read arbitrary filesystem locations. - Be aware of the 'Smart Fill' behavior: the skill can supplement missing items (marked with ⚠️) which could lead to fabricated entries; if you need strictly factual output, disable supplementing behavior or require manual review. If you want to proceed: run the code locally in a restricted environment, manually install Playwright and Chromium, inspect all scripts (especially any new scripts that would modify crontab or other system state), and only opt into automation after understanding and approving the exact crontab command and scripts involved.

功能分析

Type: OpenClaw Skill Name: content-system-news-aggregator-skill Version: 1.0.0 The news-aggregator-skill is a comprehensive tool for fetching and summarizing news from over 28 sources, including Hacker News, GitHub, and various AI newsletters. The code utilizes standard Python libraries (requests, BeautifulSoup) and Playwright (in scripts like fetch_hf_papers_playwright.py) to bypass scraping protections, which is consistent with its stated purpose. While the implementation_plan.md suggests using crontab for scheduling, this is presented transparently as a feature for automated reporting. No evidence of data exfiltration, malicious command execution, or harmful prompt injection was found; the instructions in SKILL.md and the instructions/ directory are focused on improving report quality and preventing AI hallucination.

能力标签

crypto

能力评估

ℹ Purpose & Capability

Name/description match what the code does: many fetchers, Playwright-based deep fetch, and report generation for 28 sources. The README claims 'zero-config' (no API keys) which aligns with the code (no required env vars), but the project does require system-level dependencies (Playwright + Chromium) not declared in registry metadata — mismatch between claimed 'instruction-only/zero-config' and real installation needs.

⚠ Instruction Scope

SKILL.md instructs the agent to fetch sites, enrich content, translate to Simplified Chinese, save reports to disk, and run an interactive menu triggered by a magic phrase. It also contains rules that permit 'Smart Fill' supplementation when results are scarce (potentially fabricating items even though other rules say 'Only use data from JSON'), and it mandates always saving reports to reports/YYYY-MM-DD/. MISTAKES.md documents past behavior where the maintainer read arbitrary files (root artifacts) — indicating the runtime workflow has previously included searching the filesystem for data. These broaden the skill's scope beyond pure fetching/formatting and increase risk of unwanted reads/writes or hallucinated output.

⚠ Install Mechanism

Registry lists no install spec, but the bundle contains Python scripts that require dependencies and Playwright (README and SKILL.md instruct pip install -r requirements.txt and 'playwright install chromium'). The lack of a formal install entry in registry metadata is inconsistent: users/agents may run code without ensuring dependencies are installed. implementation_plan.md proposes adding a crontab and new scripts (daily_scan.sh, generate_basic_report.py) that are not present in the manifest — this discrepancy is notable and raises risk because scheduling/persistence is being proposed but not implemented in the published package.

✓ Credentials

No environment variables, API keys, or config paths are requested in the registry metadata. The code uses public HTTP endpoints and scraping; it does not request secrets. This is proportionate to a news aggregator's purpose.

ℹ Persistence & Privilege

The skill as published does not set always:true and does not require model-disable. However implementation_plan.md explicitly asks the user to approve installing a cron job for daily automated scans (this would be a persistence/privilege escalation if installed). That cron proposal appears in a plan file rather than in active code, so it's not yet enforced — still, it's a clear request that would require elevated permission and explicit user approval before being enabled.

版本历史

v1.0.0

Publish auxiliary content-system skills

元数据

Slug content-system-news-aggregator-skill

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