content-parser

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

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 (Zero-Question Boot).

If file doesn't exist — silently create with defaults and proceed:

mkdir -p ".listenhub/content-parser"
echo '{"autoDownload":true}' > ".listenhub/content-parser/config.json"
CONFIG_PATH=".listenhub/content-parser/config.json"
CONFIG=$(cat "$CONFIG_PATH")

Do NOT ask any setup questions. Proceed directly to the Interaction Flow.

If file exists — read config silently and proceed:

CONFIG_PATH=".listenhub/content-parser/config.json"
[ ! -f "$CONFIG_PATH" ] && CONFIG_PATH="$HOME/.listenhub/content-parser/config.json"
CONFIG=$(cat "$CONFIG_PATH")

Setup Flow (user-initiated reconfigure only)

Only run when the user explicitly asks to reconfigure. Display current settings:

当前配置 (content-parser)：
  自动下载：{是 / 否}

Then ask:

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)

2. Build request body:

   jsonCopy

   {
     "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:

   bashCopy

   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 $LISTENHUB_API_KEY" \
       -H "X-Source: skills" 2>/dev/null)
     STATUS=$(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, generate a slug from the extracted title (falling back to domain name if no title). Follow shared/config-pattern.md § Artifact Naming for slug generation and dedup.

   • Write {slug}.md to the current directory — full extracted content in markdown
   • Write {slug}.json to the current directory — full raw API response data
   bashCopy

   SLUG="{title-slug}"  # e.g. "topology-wikipedia"
   # Dedup: check if files exist
   BASE="$SLUG"; i=2
   while [ -e "${SLUG}.md" ] || [ -e "${SLUG}.json" ]; do SLUG="${BASE}-${i}"; i=$((i+1)); done
   echo "$CONTENT_MD" > "${SLUG}.md"
   echo "$RESULT" > "${SLUG}.json"
   

   Present:

   Copy

   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：
     {slug}.md
     {slug}.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" \
  -H "X-Source: skills" \
  -d '{
    "source": {
      "type": "url",
      "uri": "https://en.wikipedia.org/wiki/Topology"
    }
  }'

4. Poll until complete:

curl -sS "https://api.marswave.ai/openapi/v1/content/extract/69a7dac700cf95938f86d9bb" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY" \
  -H "X-Source: skills"

5. 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" \
  -H "X-Source: skills" \
  -d '{
    "source": {
      "type": "url",
      "uri": "https://x.com/elonmusk"
    },
    "options": {
      "twitter": {
        "count": 50
      }
    }
  }'

4. Poll until complete, present results.