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0xfango

Content Parser

by 0xFango · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install content-parser
Description
Extract and parse content from URLs. Triggers on: user provides a URL to extract content from, another skill needs to parse source material, "parse this URL"...
README (SKILL.md)

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

\x3CHARD-GATE> 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. \x3C/HARD-GATE>

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)

  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="\x3Cid-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.
Usage Guidance
Don't install blindly. Before proceeding, ask the skill author (or registry owner) to clarify: (1) which API host is authoritative (is LISTENHUB backed by marswave.ai?); (2) where config and downloaded files will actually be stored (the SKILL.md both creates and forbids .listenhub); and (3) provide the missing shared files referenced (authentication.md, config-pattern.md, common-patterns.md, api-content-extract.md). If you must try it, use a throwaway/limited API key with only needed scope, run the skill in an isolated environment or container, and verify all network endpoints (DNS/IP) and files the agent writes. If the author cannot explain the domain/credential mismatch and the contradictory config instructions, treat the skill as untrusted.
Capability Analysis
Type: OpenClaw Skill Name: content-parser Version: 0.1.0 The 'content-parser' skill is a legitimate tool designed to extract and normalize content from various URLs (YouTube, Twitter, WeChat, etc.) using the Marswave API (api.marswave.ai). The skill follows a transparent workflow that includes API key validation, user confirmation for extraction options, and local storage of results in markdown and JSON formats. While it utilizes bash scripts for polling task status, the logic is restricted to the stated purpose and lacks any indicators of malicious intent, data exfiltration, or unauthorized system access.
Capability Assessment
Purpose & Capability
The skill declares it needs a LISTENHUB_API_KEY which fits a content-extraction service, but the runtime instructions call an API at https://api.marswave.ai/... — the domain does not match the LISTENHUB name and there is no homepage or source to explain this. That mismatch (credential name vs. endpoint host) is unexpected and should be justified.
Instruction Scope
SKILL.md instructs the agent to call external extraction endpoints (via curl) and to create/read local config. It also mandates reading several shared files (shared/authentication.md, shared/config-pattern.md, shared/common-patterns.md) which are not included in the package. There is a direct contradiction: Setup Flow creates files under .listenhub/ but a Hard Constraint says 'Never save files to ... .listenhub/ — save to the current working directory.' These inconsistencies could cause incorrect behavior or unexpected writes.
Install Mechanism
This is an instruction-only skill with no install spec and no bundled code, so nothing will be downloaded or written by an installer step. That is the lowest install risk.
Credentials
The skill asks for a single API credential (LISTENHUB_API_KEY), which is reasonable for a hosted extraction service. However, the env var name does not match the explicit API host used in curl calls (marswave.ai), which is suspicious and should be clarified. The SKILL.md otherwise does not request additional unrelated secrets.
Persistence & Privilege
The skill instructs creating a local config file ('.listenhub/content-parser/config.json' or $HOME equivalent) and may write extracted content into the current directory. The contradictory guidance about never saving to .listenhub vs. creating .listenhub is alarming: the skill both instructs and forbids writing there. Persisting config and output files is plausible for this functionality but the inconsistency increases risk and should be resolved.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install content-parser
  3. After installation, invoke the skill by name or use /content-parser
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
content-parser v0.1.0 - Initial release. - Extracts and parses content from URLs, supporting both user and skill-triggered flows. - Interactive setup with configurable auto-download and extraction options (summarize, maxLength, Twitter count). - Polling and background job handling for extraction tasks. - Saves results (`.md` and `.json`) to the current directory if autoDownload is enabled. - Presents extraction previews and offers next-step actions.
Metadata
Slug content-parser
Version 0.1.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Content Parser?

Extract and parse content from URLs. Triggers on: user provides a URL to extract content from, another skill needs to parse source material, "parse this URL"... It is an AI Agent Skill for Claude Code / OpenClaw, with 288 downloads so far.

How do I install Content Parser?

Run "/install content-parser" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Content Parser free?

Yes, Content Parser is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Content Parser support?

Content Parser is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Content Parser?

It is built and maintained by 0xFango (@0xfango); the current version is v0.1.0.

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