{
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  "item": {
    "slug": "news-aggregator-skill-3",
    "name": "News Aggregator Skill",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/AdministratorFung/news-aggregator-skill-3",
    "canonicalUrl": "https://clawhub.ai/AdministratorFung/news-aggregator-skill-3",
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    "sourcePlatform": "tencent",
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    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
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    "packageFormat": "ZIP package",
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      "SKILL.md",
      "requirements.txt",
      "scripts/fetch_news.py",
      "templates.md"
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      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
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      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
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      ]
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      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
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        "redirectLocation": null,
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      },
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      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/news-aggregator-skill-3"
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        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/news-aggregator-skill-3",
    "agentPageUrl": "https://openagent3.xyz/skills/news-aggregator-skill-3/agent",
    "manifestUrl": "https://openagent3.xyz/skills/news-aggregator-skill-3/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/news-aggregator-skill-3/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "News Aggregator Skill",
        "body": "Fetch real-time hot news from multiple sources."
      },
      {
        "title": "fetch_news.py",
        "body": "Usage:\n\n### Single Source (Limit 10)\n```bash\n### Global Scan (Option 12) - **Broad Fetch Strategy**\n> **NOTE**: This strategy is specifically for the \"Global Scan\" scenario where we want to catch all trends.\n\n```bash\n#  1. Fetch broadly (Massive pool for Semantic Filtering)\npython3 scripts/fetch_news.py --source all --limit 15 --deep\n\n# 2. SEMANTIC FILTERING:\n# Agent manually filters the broad list (approx 120 items) for user's topics."
      },
      {
        "title": "Single Source & Combinations (Smart Keyword Expansion)",
        "body": "CRITICAL: You MUST automatically expand the user's simple keywords to cover the entire domain field.\n\nUser: \"AI\" -> Agent uses: --keyword \"AI,LLM,GPT,Claude,Generative,Machine Learning,RAG,Agent\"\nUser: \"Android\" -> Agent uses: --keyword \"Android,Kotlin,Google,Mobile,App\"\nUser: \"Finance\" -> Agent uses: --keyword \"Finance,Stock,Market,Economy,Crypto,Gold\"\n\n# Example: User asked for \"AI news from HN\" (Note the expanded keywords)\npython3 scripts/fetch_news.py --source hackernews --limit 20 --keyword \"AI,LLM,GPT,DeepSeek,Agent\" --deep"
      },
      {
        "title": "Specific Keyword Search",
        "body": "Only use --keyword for very specific, unique terms (e.g., \"DeepSeek\", \"OpenAI\").\n\npython3 scripts/fetch_news.py --source all --limit 10 --keyword \"DeepSeek\" --deep\n\nArguments:\n\n--source: One of hackernews, weibo, github, 36kr, producthunt, v2ex, tencent, wallstreetcn, all.\n--limit: Max items per source (default 10).\n--keyword: Comma-separated filters (e.g. \"AI,GPT\").\n--deep: [NEW] Enable deep fetching. Downloads and extracts the main text content of the articles.\n\nOutput:\nJSON array. If --deep is used, items will contain a content field associated with the article text."
      },
      {
        "title": "Interactive Menu",
        "body": "When the user says \"news-aggregator-skill 如意如意\" (or similar \"menu/help\" triggers):\n\nREAD the content of templates.md in the skill directory.\nDISPLAY the list of available commands to the user exactly as they appear in the file.\nGUIDE the user to select a number or copy the command to execute."
      },
      {
        "title": "Smart Time Filtering & Reporting (CRITICAL)",
        "body": "If the user requests a specific time window (e.g., \"past X hours\") and the results are sparse (< 5 items):\n\nPrioritize User Window: First, list all items that strictly fall within the user's requested time (Time < X).\nSmart Fill: If the list is short, you MUST include high-value/high-heat items from a wider range (e.g. past 24h) to ensure the report provides at least 5 meaningful insights.\nAnnotation: Clearly mark these older items (e.g., \"⚠️ 18h ago\", \"🔥 24h Hot\") so the user knows they are supplementary.\nHigh Value: Always prioritize \"SOTA\", \"Major Release\", or \"High Heat\" items even if they slightly exceed the time window.\nGitHub Trending Exception: For purely list-based sources like GitHub Trending, strictly return the valid items from the fetched list (e.g. Top 10). List ALL fetched items. Do NOT perform \"Smart Fill\".\n\nDeep Analysis (Required): For EACH item, you MUST leverage your AI capabilities to analyze:\n\nCore Value (核心价值): What specific problem does it solve? Why is it trending?\nInspiration (启发思考): What technical or product insights can be drawn?\nScenarios (场景标签): 3-5 keywords (e.g. #RAG #LocalFirst #Rust)."
      },
      {
        "title": "6. Response Guidelines (CRITICAL)",
        "body": "Format & Style:\n\nLanguage: Simplified Chinese (简体中文).\nStyle: Magazine/Newsletter style (e.g., \"The Economist\" or \"Morning Brew\" vibe). Professional, concise, yet engaging.\nStructure:\n\nGlobal Headlines: Top 3-5 most critical stories across all domains.\nTech & AI: Specific section for AI, LLM, and Tech items.\nFinance / Social: Other strong categories if relevant.\n\n\nItem Format:\n\nTitle: MUST be a Markdown Link to the original URL.\n\n✅ Correct: ### 1. [OpenAI Releases GPT-5](https://...)\n❌ Incorrect: ### 1. OpenAI Releases GPT-5\n\n\nMetadata Line: Must include Source, Time/Date, and Heat/Score.\n1-Liner Summary: A punchy, \"so what?\" summary.\nDeep Interpretation (Bulleted): 2-3 bullet points explaining why this matters, technical details, or context. (Required for \"Deep Scan\").\n\nOutput Artifact:\n\nAlways save the full report to reports/ directory with a timestamped filename (e.g., reports/hn_news_YYYYMMDD_HHMM.md).\nPresent the full report content to the user in the chat."
      }
    ],
    "body": "News Aggregator Skill\n\nFetch real-time hot news from multiple sources.\n\nTools\nfetch_news.py\n\nUsage:\n\n### Single Source (Limit 10)\n```bash\n### Global Scan (Option 12) - **Broad Fetch Strategy**\n> **NOTE**: This strategy is specifically for the \"Global Scan\" scenario where we want to catch all trends.\n\n```bash\n#  1. Fetch broadly (Massive pool for Semantic Filtering)\npython3 scripts/fetch_news.py --source all --limit 15 --deep\n\n# 2. SEMANTIC FILTERING:\n# Agent manually filters the broad list (approx 120 items) for user's topics.\n\nSingle Source & Combinations (Smart Keyword Expansion)\n\nCRITICAL: You MUST automatically expand the user's simple keywords to cover the entire domain field.\n\nUser: \"AI\" -> Agent uses: --keyword \"AI,LLM,GPT,Claude,Generative,Machine Learning,RAG,Agent\"\nUser: \"Android\" -> Agent uses: --keyword \"Android,Kotlin,Google,Mobile,App\"\nUser: \"Finance\" -> Agent uses: --keyword \"Finance,Stock,Market,Economy,Crypto,Gold\"\n# Example: User asked for \"AI news from HN\" (Note the expanded keywords)\npython3 scripts/fetch_news.py --source hackernews --limit 20 --keyword \"AI,LLM,GPT,DeepSeek,Agent\" --deep\n\nSpecific Keyword Search\n\nOnly use --keyword for very specific, unique terms (e.g., \"DeepSeek\", \"OpenAI\").\n\npython3 scripts/fetch_news.py --source all --limit 10 --keyword \"DeepSeek\" --deep\n\n\nArguments:\n\n--source: One of hackernews, weibo, github, 36kr, producthunt, v2ex, tencent, wallstreetcn, all.\n--limit: Max items per source (default 10).\n--keyword: Comma-separated filters (e.g. \"AI,GPT\").\n--deep: [NEW] Enable deep fetching. Downloads and extracts the main text content of the articles.\n\nOutput: JSON array. If --deep is used, items will contain a content field associated with the article text.\n\nInteractive Menu\n\nWhen the user says \"news-aggregator-skill 如意如意\" (or similar \"menu/help\" triggers):\n\nREAD the content of templates.md in the skill directory.\nDISPLAY the list of available commands to the user exactly as they appear in the file.\nGUIDE the user to select a number or copy the command to execute.\nSmart Time Filtering & Reporting (CRITICAL)\n\nIf the user requests a specific time window (e.g., \"past X hours\") and the results are sparse (< 5 items):\n\nPrioritize User Window: First, list all items that strictly fall within the user's requested time (Time < X).\nSmart Fill: If the list is short, you MUST include high-value/high-heat items from a wider range (e.g. past 24h) to ensure the report provides at least 5 meaningful insights.\nAnnotation: Clearly mark these older items (e.g., \"⚠️ 18h ago\", \"🔥 24h Hot\") so the user knows they are supplementary.\nHigh Value: Always prioritize \"SOTA\", \"Major Release\", or \"High Heat\" items even if they slightly exceed the time window.\nGitHub Trending Exception: For purely list-based sources like GitHub Trending, strictly return the valid items from the fetched list (e.g. Top 10). List ALL fetched items. Do NOT perform \"Smart Fill\".\nDeep Analysis (Required): For EACH item, you MUST leverage your AI capabilities to analyze:\nCore Value (核心价值): What specific problem does it solve? Why is it trending?\nInspiration (启发思考): What technical or product insights can be drawn?\nScenarios (场景标签): 3-5 keywords (e.g. #RAG #LocalFirst #Rust).\n6. Response Guidelines (CRITICAL)\n\nFormat & Style:\n\nLanguage: Simplified Chinese (简体中文).\nStyle: Magazine/Newsletter style (e.g., \"The Economist\" or \"Morning Brew\" vibe). Professional, concise, yet engaging.\nStructure:\nGlobal Headlines: Top 3-5 most critical stories across all domains.\nTech & AI: Specific section for AI, LLM, and Tech items.\nFinance / Social: Other strong categories if relevant.\nItem Format:\nTitle: MUST be a Markdown Link to the original URL.\n✅ Correct: ### 1. [OpenAI Releases GPT-5](https://...)\n❌ Incorrect: ### 1. OpenAI Releases GPT-5\nMetadata Line: Must include Source, Time/Date, and Heat/Score.\n1-Liner Summary: A punchy, \"so what?\" summary.\nDeep Interpretation (Bulleted): 2-3 bullet points explaining why this matters, technical details, or context. (Required for \"Deep Scan\").\n\nOutput Artifact:\n\nAlways save the full report to reports/ directory with a timestamped filename (e.g., reports/hn_news_YYYYMMDD_HHMM.md).\nPresent the full report content to the user in the chat."
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/AdministratorFung/news-aggregator-skill-3",
    "publisherUrl": "https://clawhub.ai/AdministratorFung/news-aggregator-skill-3",
    "owner": "AdministratorFung",
    "version": "0.1.0",
    "license": null,
    "verificationStatus": "Indexed source record"
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}