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Agent Skill · 研究检索

tech-news-digest(科技新闻文摘)

tech-news-digest 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

tech-news-digest 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 464。

总安装 275,449周安装 11,832GitHub Stars 25下载 96,549核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
3.16.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tech-news-digest(科技新闻文摘)
来源仓库:https://github.com/dinstein/tech-news-digest
安装命令:
openclaw skills install tech-news-digest
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install tech-news-digest

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用统一源模型、质量评分和多格式输出生成科技新闻摘要。来自 RSS feed、Twitter/X KOL、Gi 的六源数据收集

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install tech-news-digest;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

tech-news-digest 怎么安装?

在终端执行 openclaw skills install tech-news-digest。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tech-news-digest 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

tech-news-digest 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

tech-news-digest 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

tech-news-digest 用的人多吗?

公开数据是累计安装 275,449 次,近一周安装 11,832 次,下载 96,549 次,GitHub 25 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

tech-news-digest 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
tech-news-digest

科技新闻文摘 · 本页

275,44925接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
tech-news-digest
description
Generate tech news digests with unified source model, quality scoring, and multi-format output. Six-source data collection from RSS feeds, Twitter/X KOLs, GitHub releases, GitHub Trending, Reddit, and web search. Pipeline-based scripts with retry mechanisms and deduplication. Supports Discord, email, and markdown templates.
version
3.16.0
homepage
https://github.com/draco-agent/tech-news-digest
source
https://github.com/draco-agent/tech-news-digest
metadata
openclaw
requires
bins
["python3"]
optionalBins
["mail", "msmtp", "gog", "gh", "openssl", "weasyprint"]
env
required
false
description
Twitter API backend: 'official', 'twitterapiio', or 'auto' (default: auto)
required
false
description
Twitter/X API bearer token for KOL monitoring (official backend)
required
false
description
twitterapi.io API key for KOL monitoring (twitterapiio backend)
required
false
description
Tavily Search API key (alternative to Brave)
required
false
description
Web search backend: auto (default), brave, or tavily
required
false
description
Brave Search API keys (comma-separated for rotation)
required
false
description
Brave Search API key (single key fallback)
required
false
description
GitHub token for higher API rate limits (auto-generated from GitHub App if not set)
required
false
description
GitHub App ID for automatic installation token generation
required
false
description
GitHub App Installation ID for automatic token generation
required
false
description
Path to GitHub App private key PEM file
tools
files
read
write

Tech News Digest

Automated tech news digest system with unified data source model, quality scoring pipeline, and template-based output generation.

Quick Start

  1. Configuration Setup: Default configs are in config/defaults/. Copy to workspace for customization:
   mkdir -p workspace/config
   cp config/defaults/sources.json workspace/config/tech-news-digest-sources.json
   cp config/defaults/topics.json workspace/config/tech-news-digest-topics.json
  1. Environment Variables:

- TWITTERAPI_IO_KEY - twitterapi.io API key (optional, preferred) - X_BEARER_TOKEN - Twitter/X official API bearer token (optional, fallback) - TAVILY_API_KEY - Tavily Search API key, alternative to Brave (optional) - WEB_SEARCH_BACKEND - Web search backend: auto|brave|tavily (optional, default: auto) - BRAVE_API_KEYS - Brave Search API keys, comma-separated for rotation (optional) - BRAVE_API_KEY - Single Brave key fallback (optional) - GITHUB_TOKEN - GitHub personal access token (optional, improves rate limits)

  1. Generate Digest:
   # Unified pipeline (recommended) — runs all 6 sources in parallel + merge
   python3 scripts/run-pipeline.py \
     --defaults config/defaults \
     --config workspace/config \
     --hours 48 --freshness pd \
     --archive-dir workspace/archive/tech-news-digest/ \
     --output /tmp/td-merged.json --verbose --force
  1. Use Templates: Apply Discord, email, or PDF templates to merged output

Configuration Files

sources.json - Unified Data Sources

{
  "sources": [
    {
      "id": "openai-rss",
      "type": "rss",
      "name": "OpenAI Blog",
      "url": "https://openai.com/blog/rss.xml",
      "enabled": true,
      "priority": true,
      "topics": ["llm", "ai-agent"],
      "note": "Official OpenAI updates"
    },
    {
      "id": "sama-twitter",
      "type": "twitter", 
      "name": "Sam Altman",
      "handle": "sama",
      "enabled": true,
      "priority": true,
      "topics": ["llm", "frontier-tech"],
      "note": "OpenAI CEO"
    }
  ]
}

topics.json - Enhanced Topic Definitions

{
  "topics": [
    {
      "id": "llm",
      "emoji": "🧠",
      "label": "LLM / Large Models",
      "description": "Large Language Models, foundation models, breakthroughs",
      "search": {
        "queries": ["LLM latest news", "large language model breakthroughs"],
        "must_include": ["LLM", "large language model", "foundation model"],
        "exclude": ["tutorial", "beginner guide"]
      },
      "display": {
        "max_items": 8,
        "style": "detailed"
      }
    }
  ]
}

Scripts Pipeline

run-pipeline.py - Unified Pipeline (Recommended)

python3 scripts/run-pipeline.py \
  --defaults config/defaults [--config CONFIG_DIR] \
  --hours 48 --freshness pd \
  --archive-dir workspace/archive/tech-news-digest/ \
  --output /tmp/td-merged.json --verbose --force
  • Features: Runs all 6 fetch steps in parallel, then merges + deduplicates + scores
  • Output: Final merged JSON ready for report generation (~30s total)
  • Metadata: Saves per-step timing and counts to *.meta.json
  • GitHub Auth: Auto-generates GitHub App token if $GITHUB_TOKEN not set
  • Fallback: If this fails, run individual scripts below

Individual Scripts (Fallback)

fetch-rss.py - RSS Feed Fetcher
python3 scripts/fetch-rss.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE] [--verbose]
  • Parallel fetching (10 workers), retry with backoff, feedparser + regex fallback
  • Timeout: 30s per feed, ETag/Last-Modified caching
fetch-twitter.py - Twitter/X KOL Monitor
python3 scripts/fetch-twitter.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE] [--backend auto|official|twitterapiio]
  • Backend auto-detection: uses twitterapi.io if TWITTERAPI_IO_KEY set, else official X API v2 if X_BEARER_TOKEN set
  • Rate limit handling, engagement metrics, retry with backoff
fetch-web.py - Web Search Engine
python3 scripts/fetch-web.py [--defaults DIR] [--config DIR] [--freshness pd] [--output FILE]
  • Auto-detects Brave API rate limit: paid plans → parallel queries, free → sequential
  • Without API: generates search interface for agents
fetch-github.py - GitHub Releases Monitor
python3 scripts/fetch-github.py [--defaults DIR] [--config DIR] [--hours 168] [--output FILE]
  • Parallel fetching (10 workers), 30s timeout
  • Auth priority: $GITHUB_TOKEN → GitHub App auto-generate → gh CLI → unauthenticated (60 req/hr)
fetch-github.py --trending - GitHub Trending Repos
python3 scripts/fetch-github.py --trending [--hours 48] [--output FILE] [--verbose]
  • Searches GitHub API for trending repos across 4 topics (LLM, AI Agent, Crypto, Frontier Tech)
  • Quality scoring: base 5 + daily_stars_est / 10, max 15
fetch-reddit.py - Reddit Posts Fetcher
python3 scripts/fetch-reddit.py [--defaults DIR] [--config DIR] [--hours 48] [--output FILE]
  • Parallel fetching (4 workers), public JSON API (no auth required)
  • 13 subreddits with score filtering
enrich-articles.py - Article Full-Text Enrichment
python3 scripts/enrich-articles.py --input merged.json --output enriched.json [--min-score 10] [--max-articles 15] [--verbose]
  • Fetches full article text for high-scoring articles
  • Cloudflare Markdown for Agents (preferred) → HTML extraction (fallback) → Skip (paywalled/social)
  • Blog domain whitelist with lower score threshold (≥3)
  • Parallel fetching (5 workers, 10s timeout)
merge-sources.py - Quality Scoring & Deduplication
python3 scripts/merge-sources.py --rss FILE --twitter FILE --web FILE --github FILE --reddit FILE
  • Quality scoring, title similarity dedup (85%), previous digest penalty
  • Output: topic-grouped articles sorted by score
validate-config.py - Configuration Validator
python3 scripts/validate-config.py [--defaults DIR] [--config DIR] [--verbose]
  • JSON schema validation, topic reference checks, duplicate ID detection
generate-pdf.py - PDF Report Generator
python3 scripts/generate-pdf.py --input report.md --output digest.pdf [--verbose]
  • Converts markdown digest to styled A4 PDF with Chinese typography (Noto Sans CJK SC)
  • Emoji icons, page headers/footers, blue accent theme. Requires weasyprint.
sanitize-html.py - Safe HTML Email Converter
python3 scripts/sanitize-html.py --input report.md --output email.html [--verbose]
  • Converts markdown to XSS-safe HTML email with inline CSS
  • URL whitelist (http/https only), HTML-escaped text content
source-health.py - Source Health Monitor
python3 scripts/source-health.py --rss FILE --twitter FILE --github FILE --reddit FILE --web FILE [--verbose]
  • Tracks per-source success/failure history over 7 days
  • Reports unhealthy sources (>50% failure rate)
summarize-merged.py - Merged Data Summary
python3 scripts/summarize-merged.py --input merged.json [--top N] [--topic TOPIC]
  • Human-readable summary of merged data for LLM consumption
  • Shows top articles per topic with scores and metrics

User Customization

Workspace Configuration Override

Place custom configs in workspace/config/ to override defaults:

  • Sources: Append new sources, disable defaults with "enabled": false
  • Topics: Override topic definitions, search queries, display settings
  • Merge Logic:

- Sources with same id → user version takes precedence - Sources with new id → appended to defaults - Topics with same id → user version completely replaces default

Example Workspace Override

// workspace/config/tech-news-digest-sources.json
{
  "sources": [
    {
      "id": "simonwillison-rss",
      "enabled": false,
      "note": "Disabled: too noisy for my use case"
    },
    {
      "id": "my-custom-blog", 
      "type": "rss",
      "name": "My Custom Tech Blog",
      "url": "https://myblog.com/rss",
      "enabled": true,
      "priority": true,
      "topics": ["frontier-tech"]
    }
  ]
}

Templates & Output

Discord Template (references/templates/discord.md)

  • Bullet list format with link suppression (<link>)
  • Mobile-optimized, emoji headers
  • 2000 character limit awareness

Email Template (references/templates/email.md)

  • Rich metadata, technical stats, archive links
  • Executive summary, top articles section
  • HTML-compatible formatting

PDF Template (references/templates/pdf.md)

  • A4 layout with Noto Sans CJK SC font for Chinese support
  • Emoji icons, page headers/footers with page numbers
  • Generated via scripts/generate-pdf.py (requires weasyprint)

Default Sources (151 total)

  • RSS Feeds (62): AI labs, tech blogs, crypto news, Chinese tech media
  • Twitter/X KOLs (48): AI researchers, crypto leaders, tech executives
  • GitHub Repos (28): Major open-source projects (LangChain, vLLM, DeepSeek, Llama, etc.)
  • Reddit (13): r/MachineLearning, r/LocalLLaMA, r/CryptoCurrency, r/ChatGPT, r/OpenAI, etc.
  • Web Search (4 topics): LLM, AI Agent, Crypto, Frontier Tech

All sources pre-configured with appropriate topic tags and priority levels.

Dependencies

pip install -r requirements.txt

Optional but Recommended:

  • feedparser>=6.0.0 - Better RSS parsing (fallback to regex if unavailable)
  • jsonschema>=4.0.0 - Configuration validation

All scripts work with Python 3.8+ standard library only.

Monitoring & Operations

Health Checks

# Validate configuration
python3 scripts/validate-config.py --verbose

# Test RSS feeds
python3 scripts/fetch-rss.py --hours 1 --verbose

# Check Twitter API
python3 scripts/fetch-twitter.py --hours 1 --verbose

Archive Management

  • Digests automatically archived to <workspace>/archive/tech-news-digest/
  • Previous digest titles used for duplicate detection
  • Old archives cleaned automatically (90+ days)

Error Handling

  • Network Failures: Retry with exponential backoff
  • Rate Limits: Automatic retry with appropriate delays
  • Invalid Content: Graceful degradation, detailed logging
  • Configuration Errors: Schema validation with helpful messages

API Keys & Environment

Set in ~/.zshenv or similar:

# Twitter (at least one required for Twitter source)
export TWITTERAPI_IO_KEY="your_key"        # twitterapi.io key (preferred)
export X_BEARER_TOKEN="your_bearer_token"  # Official X API v2 (fallback)
export TWITTER_API_BACKEND="auto"          # auto|twitterapiio|official (default: auto)

# Web Search (optional, enables web search layer)
export WEB_SEARCH_BACKEND="auto"          # auto|brave|tavily (default: auto)
export TAVILY_API_KEY="tvly-xxx"           # Tavily Search API (free 1000/mo)

# Brave Search (alternative)
export BRAVE_API_KEYS="key1,key2,key3"     # Multiple keys, comma-separated rotation
export BRAVE_API_KEY="key1"                # Single key fallback
export BRAVE_PLAN="free"                   # Override rate limit detection: free|pro

# GitHub (optional, improves rate limits)
export GITHUB_TOKEN="ghp_xxx"              # PAT (simplest)
export GH_APP_ID="12345"                   # Or use GitHub App for auto-token
export GH_APP_INSTALL_ID="67890"
export GH_APP_KEY_FILE="/path/to/key.pem"
  • Twitter: TWITTERAPI_IO_KEY preferred ($3-5/mo); X_BEARER_TOKEN as fallback; auto mode tries twitterapiio first
  • Web Search: Tavily (preferred in auto mode) or Brave; optional, fallback to agent web_search if unavailable
  • GitHub: Auto-generates token from GitHub App if PAT not set; unauthenticated fallback (60 req/hr)
  • Reddit: No API key needed (uses public JSON API)

Cron / Scheduled Task Integration

OpenClaw Cron (Recommended)

The cron prompt should NOT hardcode the pipeline steps. Instead, reference references/digest-prompt.md and only pass configuration parameters. This ensures the pipeline logic stays in the skill repo and is consistent across all installations.

Daily Digest Cron Prompt
Read <SKILL_DIR>/references/digest-prompt.md and follow the complete workflow to generate a daily digest.

Replace placeholders with:
- MODE = daily
- TIME_WINDOW = past 1-2 days
- FRESHNESS = pd
- RSS_HOURS = 48
- ITEMS_PER_SECTION = 3-5
- ENRICH = true
- BLOG_PICKS_COUNT = 3
- EXTRA_SECTIONS = (none)
- SUBJECT = Daily Tech Digest - YYYY-MM-DD
- WORKSPACE = <your workspace path>
- SKILL_DIR = <your skill install path>
- DISCORD_CHANNEL_ID = <your channel id>
- EMAIL = (optional)
- LANGUAGE = English
- TEMPLATE = discord

Follow every step in the prompt template strictly. Do not skip any steps.
Weekly Digest Cron Prompt
Read <SKILL_DIR>/references/digest-prompt.md and follow the complete workflow to generate a weekly digest.

Replace placeholders with:
- MODE = weekly
- TIME_WINDOW = past 7 days
- FRESHNESS = pw
- RSS_HOURS = 168
- ITEMS_PER_SECTION = 10-15
- ENRICH = true
- BLOG_PICKS_COUNT = 3-5
- EXTRA_SECTIONS = 📊 Weekly Trend Summary (2-3 sentences summarizing macro trends)
- SUBJECT = Weekly Tech Digest - YYYY-MM-DD
- WORKSPACE = <your workspace path>
- SKILL_DIR = <your skill install path>
- DISCORD_CHANNEL_ID = <your channel id>
- EMAIL = (optional)
- LANGUAGE = English
- TEMPLATE = discord

Follow every step in the prompt template strictly. Do not skip any steps.
Why This Pattern?
  • Single source of truth: Pipeline logic lives in digest-prompt.md, not scattered across cron configs
  • Portable: Same skill on different OpenClaw instances, just change paths and channel IDs
  • Maintainable: Update the skill → all cron jobs pick up changes automatically
  • Anti-pattern: Do NOT copy pipeline steps into the cron prompt — it will drift out of sync
Multi-Channel Delivery Limitation

OpenClaw enforces cross-provider isolation: a single session can only send messages to one provider (e.g., Discord OR Telegram, not both). If you need to deliver digests to multiple platforms, create separate cron jobs for each provider:

# Job 1: Discord + Email
- DISCORD_CHANNEL_ID = <your-discord-channel-id>
- EMAIL = user@example.com
- TEMPLATE = discord

# Job 2: Telegram DM
- DISCORD_CHANNEL_ID = (none)
- EMAIL = (none)
- TEMPLATE = telegram

Replace DISCORD_CHANNEL_ID delivery with the target platform's delivery in the second job's prompt.

This is a security feature, not a bug — it prevents accidental cross-context data leakage.

Security Notes

Execution Model

This skill uses a prompt template pattern: the agent reads digest-prompt.md and follows its instructions. This is the standard OpenClaw skill execution model — the agent interprets structured instructions from skill-provided files. All instructions are shipped with the skill bundle and can be audited before installation.

Network Access

The Python scripts make outbound requests to:

  • RSS feed URLs (configured in tech-news-digest-sources.json)
  • Twitter/X API (api.x.com or api.twitterapi.io)
  • Brave Search API (api.search.brave.com)
  • Tavily Search API (api.tavily.com)
  • GitHub API (api.github.com)
  • Reddit JSON API (reddit.com)

No data is sent to any other endpoints. All API keys are read from environment variables declared in the skill metadata.

Shell Safety

Email delivery uses send-email.py which constructs proper MIME multipart messages with HTML body + optional PDF attachment. Subject formats are hardcoded (Daily Tech Digest - YYYY-MM-DD). PDF generation uses generate-pdf.py via weasyprint. The prompt template explicitly prohibits interpolating untrusted content (article titles, tweet text, etc.) into shell arguments. Email addresses and subjects must be static placeholder values only.

File Access

Scripts read from config/ and write to workspace/archive/. No files outside the workspace are accessed.

Support & Troubleshooting

Common Issues

  1. RSS feeds failing: Check network connectivity, use --verbose for details
  2. Twitter rate limits: Reduce sources or increase interval
  3. Configuration errors: Run validate-config.py for specific issues
  4. No articles found: Check time window (--hours) and source enablement

Debug Mode

All scripts support --verbose flag for detailed logging and troubleshooting.

Performance Tuning

  • Parallel Workers: Adjust MAX_WORKERS in scripts for your system
  • Timeout Settings: Increase TIMEOUT for slow networks
  • Article Limits: Adjust MAX_ARTICLES_PER_FEED based on needs

Security Considerations

Shell Execution

The digest prompt instructs agents to run Python scripts via shell commands. All script paths and arguments are skill-defined constants — no user input is interpolated into commands. Two scripts use subprocess:

  • run-pipeline.py orchestrates child fetch scripts (all within scripts/ directory)
  • fetch-github.py has two subprocess calls:

1. openssl dgst -sha256 -sign for JWT signing (only if GH_APP_* env vars are set — signs a self-constructed JWT payload, no user content involved) 2. gh auth token CLI fallback (only if gh is installed — reads from gh's own credential store)

No user-supplied or fetched content is ever interpolated into subprocess arguments. Email delivery uses send-email.py which builds MIME messages programmatically — no shell interpolation. PDF generation uses generate-pdf.py via weasyprint. Email subjects are static format strings only — never constructed from fetched data.

Credential & File Access

Scripts do not directly read ~/.config/, ~/.ssh/, or any credential files. All API tokens are read from environment variables declared in the skill metadata. The GitHub auth cascade is:

  1. $GITHUB_TOKEN env var (you control what to provide)
  2. GitHub App token generation (only if you set GH_APP_ID, GH_APP_INSTALL_ID, and GH_APP_KEY_FILE — uses inline JWT signing via openssl CLI, no external scripts involved)
  3. gh auth token CLI (delegates to gh's own secure credential store)
  4. Unauthenticated (60 req/hr, safe fallback)

If you prefer no automatic credential discovery, simply set $GITHUB_TOKEN and the script will use it directly without attempting steps 2-3.

Dependency Installation

This skill does not install any packages. requirements.txt lists optional dependencies (feedparser, jsonschema) for reference only. All scripts work with Python 3.8+ standard library. Users should install optional deps in a virtualenv if desired — the skill never runs pip install.

Input Sanitization

  • URL resolution rejects non-HTTP(S) schemes (javascript:, data:, etc.)
  • RSS fallback parsing uses simple, non-backtracking regex patterns (no ReDoS risk)
  • All fetched content is treated as untrusted data for display only

Network Access

Scripts make outbound HTTP requests to configured RSS feeds, Twitter API, GitHub API, Reddit JSON API, Brave Search API, and Tavily Search API. No inbound connections or listeners are created.

平台分布

OpenClaw

75.25%
按下载量换算72,653

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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