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Content Parser,数据分析 Content Parser 下载,Content Parser skills,AI Content Parser 下载 · 小葱技能站 免费的AI skills 下载

Content Parser

👤 0xfango 📦 v0.1.0 ⭐ 4.5 ⬇️ 764 下载
📊 数据分析 免费 🔑 需 API Key

📖 技能介绍

When to Use

  • User provides a URL and wants to extract/read its content
  • Another skill needs to parse source material from a URL before generation
  • User says "parse this URL", "extract content from this link"
  • User says "解析链接", "提取内容"

When NOT to Use

  • User already has text content and doesn't need URL parsing
  • User wants to generate audio/video content (not content extraction)
  • User wants to read a local file (use standard file reading tools)

Purpose

Extract and normalize content from URLs across supported platforms. Returns structured data including content body, metadata, and references. Useful as a preprocessing step for content generation skills or standalone content extraction.

Hard Constraints

  • No shell scripts. Construct curl commands from the API reference files listed in Resources
  • Always read shared/authentication.md for API key and headers
  • Follow shared/common-patterns.md for polling, errors, and interaction patterns
  • URL must be a valid HTTP(S) URL
  • Always read config following shared/config-pattern.md before any interaction
  • Never save files to ~/Downloads/ or .listenhub/ — save to the current working directory
Use the AskUserQuestion tool for every multiple-choice step — do NOT print options as plain text. Ask one question at a time. Wait for the user's answer before proceeding to the next step. After collecting URL and options, confirm with the user before calling the extraction API.

Step -1: API Key Check

Follow shared/config-pattern.md § API Key Check. If the key is missing, stop immediately.

Step 0: Config Setup

Follow shared/config-pattern.md Step 0.

If file doesn't exist — ask location, then create immediately:

mkdir -p ".listenhub/content-parser"
echo '{"autoDownload":true}' > ".listenhub/content-parser/config.json"
CONFIG_PATH=".listenhub/content-parser/config.json"
# (or $HOME/.listenhub/content-parser/config.json for global)

Then run Setup Flow below.

If file exists — read config, display summary, and confirm:

当前配置 (content-parser):
  自动下载:{是 / 否}

Ask: "使用已保存的配置?" → 确认,直接继续 / 重新配置

Setup Flow (first run or reconfigure)

  1. autoDownload: "自动保存提取的内容到当前目录?"
    • "是(推荐)" → autoDownload: true
    • "否" → autoDownload: false

Save immediately:

NEW_CONFIG=$(echo "$CONFIG" | jq --argjson dl {true/false} '. + {"autoDownload": $dl}')
echo "$NEW_CONFIG" > "$CONFIG_PATH"
CONFIG=$(cat "$CONFIG_PATH")

Interaction Flow

Step 1: URL Input

Free text input. Ask the user:

What URL would you like to extract content from?

Step 2: Options (optional)

Ask if the user wants to configure extraction options:

Question: "Do you want to configure extraction options?"
Options:
  - "No, use defaults" — Extract with default settings
  - "Yes, configure options" — Set summarize, maxLength, or Twitter tweet count

If "Yes", ask follow-up questions:

  • Summarize: "Generate a summary of the content?" (Yes/No)
  • Max Length: "Set maximum content length?" (Free text, e.g., "5000")
  • Twitter count (only if URL is Twitter/X profile): "How many tweets to fetch?" (1-100, default 20)

Step 3: Confirm & Extract

Summarize:

Ready to extract content:

  URL: {url}
  Options: {summarize: true, maxLength: 5000, twitter.count: 50} / default

  Proceed?

Wait for explicit confirmation before calling the API.

Workflow

  1. Validate URL: Must be HTTP(S). Normalize if needed (see references/supported-platforms.md)

    小葱技能7w4.net有更新,你可以访问看下。

  2. Build request body:

    {
     "source": {
       "type": "url",
       "uri": "{url}"
     },
     "options": {
       "summarize": true/false,
       "maxLength": 5000,
       "twitter": {
         "count": 50
       }
     }
    }

    Omit options if user chose defaults.

  3. Submit (foreground): POST /v1/content/extract → extract taskId

  4. Tell the user extraction is in progress

  5. Poll (background): Run the following exact bash command with run_in_background: true and timeout: 300000. Note: status field is .data.status (not processStatus), interval is 5s, values are processing/completed/failed:

    TASK_ID="<id-from-step-3>"
    for i in $(seq 1 60); do
     RESULT=$(curl -sS "https://api.marswave.ai/openapi/v1/content/extract/$TASK_ID" \
       -H "Authorization: Bearer $LISTENHUB_API_KEY" 2>/dev/null)
     STATUS=$(echo "$RESULT" | tr -d '\000-\037\177' | jq -r '.data.status // "processing"')
     case "$STATUS" in
       completed) echo "$RESULT"; exit 0 ;;
       failed) echo "FAILED: $RESULT" >&2; exit 1 ;;
       *) sleep 5 ;;
     esac
    done
    echo "TIMEOUT" >&2; exit 2
  6. When notified, download and present result:

    If autoDownload is true:

    • Write {taskId}-extracted.md to the current directory — full extracted content in markdown
    • Write {taskId}-extracted.json to the current directory — full raw API response data
    echo "$CONTENT_MD" > "${TASK_ID}-extracted.md"
    echo "$RESULT" > "${TASK_ID}-extracted.json"

    Present:

    内容提取完成!
    
    来源:{url}
    标题:{metadata.title}
    长度:~{character count} 字符
    消耗积分:{credits}
    
    已保存到当前目录:
     {taskId}-extracted.md
     {taskId}-extracted.json
  7. Show a preview of the extracted content (first ~500 chars)

  8. Offer to use content in another skill (e.g. /podcast, /tts)

Estimated time: 10-30 seconds depending on content size and platform.

API Reference

  • Content extract: shared/api-content-extract.md
  • Supported platforms: references/supported-platforms.md
  • Polling: shared/common-patterns.md § Async Polling
  • Error handling: shared/common-patterns.md § Error Handling
  • Config pattern: shared/config-pattern.md

Example

User: "Parse this article: https://en.wikipedia.org/wiki/Topology"

Agent workflow:

  1. URL: https://en.wikipedia.org/wiki/Topology
  2. Options: defaults (omit options)
  3. Submit extraction
curl -sS -X POST "https://api.marswave.ai/openapi/v1/content/extract" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "source": {
      "type": "url",
      "uri": "https://en.wikipedia.org/wiki/Topology"
    }
  }'
  1. Poll until complete:
curl -sS "https://api.marswave.ai/openapi/v1/content/extract/69a7dac700cf95938f86d9bb" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY"
  1. Present extracted content preview and offer next actions.

User: "Extract recent tweets from @elonmusk, get 50 tweets"

Agent workflow:

  1. URL: https://x.com/elonmusk
  2. Options: {"twitter": {"count": 50}}
  3. Submit extraction
curl -sS -X POST "https://api.marswave.ai/openapi/v1/content/extract" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "source": {
      "type": "url",
      "uri": "https://x.com/elonmusk"
    },
    "options": {
      "twitter": {
        "count": 50
      }
    }
  }'
  1. Poll until complete, present results.

🤖 AI 评测

这是一款实用的内容提取工具,能快速从网页、视频、社交媒体等多种来源获取所需内容,支持多个主流平台,操作流程简洁,每步都有确认提示,能自动生成摘要。整体质量良好,但需要配置 API 才能使用,对非技术用户有一定门槛,且部分平台内容可能存在限制。

📊 多维度评分

适应性4.7
规范性4.3
有效性4.7
可靠性4.2
可信度4.7

📁 包含文件 (3 个)

📄 SKILL.md 7.5 KB
📄 _meta.json 133 B
📄 references/supported-platforms.md 2.5 KB