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Agent Skill · 开发

content-parser(内容解析器)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

content-parser 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 2,478。

总安装 16,873周安装 676GitHub Stars 49下载 5,462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
unknown

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:content-parser(内容解析器)
来源仓库:https://github.com/marswaveai/skills
仓库路径:skills/content-parser
安装命令:
npx skills add https://github.com/marswaveai/skills --skill content-parser
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/marswaveai/skills --skill content-parser

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

content-parser 用于辅助文档、README、Markdown 和内容稿件的整理与改写。适合提炼结构、补齐章节、统一术语或检查链接,提升内容可读性。保留项目已有事实,不把未确认信息写成确定结论,涉及对外文案时控制语气。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/content-parser

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/marswaveai/skills --skill content-parser;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

content-parser 怎么安装?

在终端执行 npx skills add https://github.com/marswaveai/skills --skill content-parser。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

content-parser 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

content-parser 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。

content-parser 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

content-parser 用的人多吗?

公开数据是累计安装 16,873 次,近一周安装 676 次,下载 5,462 次,GitHub 49 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。

content-parser 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

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。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
content-parser

内容解析器 · 本页

16,87349接触敏感数据未明确有提醒

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

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 (Inlined) section below
  • See § API Reference (Inlined) below for API key and headers
  • See § API Reference (Inlined) below 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: {"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 $LISTENHUB_API_KEY" \ -H "X-Source: skills" 2>/dev/null) STATUS=$(echo "$RESULT" | tr -d '\000-\037\177' | jq -r '.data.status // "processing"') case "$STATUS" in completed) echo "$RESULT"; exit 0;; failed) echo "FAILED: $RESULT" >&2; exit 1;; *) sleep 5;; esac done echo "TIMEOUT" >&2; exit 2
  6. When notified, download and present result: If autoDownload is true, generate a slug from the extracted title (falling back to domain name if no title). Follow shared/config-pattern.md § Artifact Naming for slug generation and dedup. SLUG="{title-slug}" # e.g. "topology-wikipedia" # Dedup: check if files exist BASE="$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: 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

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

  1. Show a preview of the extracted content (first ~500 chars)
  2. Offer to use content in another skill (e.g. /podcast, /tts)

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

API Reference (Inlined)

Authentication

Environment variable: LISTENHUB_API_KEY (format: lh_sk_...)

Store in ~/.zshrc (macOS) or ~/.bashrc (Linux):

export LISTENHUB_API_KEY="lh_sk_..."

How to obtain: Visit https://listenhub.ai/settings/api-keys (Pro plan required).

Base URL: https://api.marswave.ai/openapi/v1

Required headers (every request):

Authorization: Bearer $LISTENHUB_API_KEY
Content-Type: application/json
X-Source: skills

The X-Source: skills header identifies requests as coming from Claude Code skills (CLI tool).

curl template:

curl -sS -X POST "https://api.marswave.ai/openapi/v1/{endpoint}" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -H "X-Source: skills" \
  -d '{ ... }'

For GET requests, omit -d and change -X POST to -X GET.

Security notes:

  • Never log or display full API keys in output
  • API keys are transmitted via HTTPS only
  • Do not pass sensitive or confidential information as content input — it is sent to external APIs for processing

POST /v1/content/extract

Create a content extraction task for a URL. Returns a taskId for polling.

Request body:

FieldRequiredTypeDescription
sourceYesobjectSource to extract from
source.typeYesstringMust be "url"
source.uriYesstringValid HTTP(S) URL to extract content from
optionsNoobjectExtraction options
options.summarizeNobooleanWhether to generate a summary
options.maxLengthNointegerMaximum content length
options.twitterNoobjectTwitter/X specific options
options.twitter.countNointegerNumber of tweets to fetch (1-100, default 20)

Response:

{
  "code": 0,
  "message": "success",
  "data": {
    "taskId": "69a7dac700cf95938f86d9bb"
  }
}

Error codes:

CodeMeaning
29003Validation error ("source.uri" is required, "source.uri" must be a valid uri)
21007Invalid API key

GET /v1/content/extract/{taskId}

Get extraction task status and results.

Path params:

ParamTypeDescription
taskIdstring24-char hex task ID

Response states:

  • processing — Task is still running
  • completed — Extraction finished, data available
  • failed — Extraction failed, check failCode and message

Response (processing):

{
  "code": 0,
  "message": "success",
  "data": {
    "taskId": "69a7dac700cf95938f86d9bb",
    "status": "processing",
    "createdAt": "2025-04-09T12:00:00Z",
    "data": null,
    "credits": 0,
    "failCode": null,
    "message": null
  }
}

Response (completed):

{
  "code": 0,
  "message": "success",
  "data": {
    "taskId": "69a7dac700cf95938f86d9bb",
    "status": "completed",
    "createdAt": "2025-04-09T12:00:00Z",
    "data": {
      "content": "Extracted text content...",
      "metadata": {
        "title": "Article Title",
        "author": "Author Name",
        "publishedAt": "2025-04-01T08:00:00Z"
      },
      "references": [
        "https://example.com/related-article"
      ]
    },
    "credits": 5,
    "failCode": null,
    "message": null
  }
}

Response (failed):

{
  "code": 0,
  "message": "success",
  "data": {
    "taskId": "69a7dac700cf95938f86d9bb",
    "status": "failed",
    "createdAt": "2025-04-09T12:00:00Z",
    "data": null,
    "credits": 0,
    "failCode": "EXTRACT_FAILED",
    "message": "Unable to extract content from the provided URL"
  }
}

Key fields:

FieldTypeDescription
statusstringprocessing, completed, or failed
data.data.contentstringExtracted text content
data.data.metadataobjectPage metadata (title, author, publishedAt)
data.data.referencesarrayReferenced URLs (array of strings)
creditsintegerCredits consumed
failCodestringError code (null on success)
messagestringError message (null on success)

Error codes:

CodeMeaning
29003Invalid taskId format
25002Task not found

Polling Pattern

5-second interval, 60 polls max. Run with run_in_background: true and timeout: 300000.

Two-step pattern:

  1. Submit (foreground): POST the creation request, extract taskId from the response.
  2. Poll (background): Run the polling loop with run_in_background: true. You will be notified automatically when it completes.

The exact polling bash command is already specified in the Workflow section (Step 5).


Error Handling

HTTP status codes:

CodeMeaningAction
200SuccessParse response body
400Bad requestCheck parameters
401Invalid API keyRe-check LISTENHUB_API_KEY
402Insufficient creditsInform user to recharge
403ForbiddenNo permission for this resource
429Rate limitedExponential backoff, retry after delay
500/502/503/504Server errorRetry up to 3 times

Retry strategy:

  • 429 rate limit: Wait 15 seconds, then retry (exponential backoff)
  • 5xx server errors: Retry up to 3 times with 5-second intervals
  • Network errors: Retry up to 3 times

Application error codes:

CodeMeaning
21007Invalid user API key
25429Rate limited (application-level)

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"
    }
  }'
  1. Poll until complete:
curl -sS "https://api.marswave.ai/openapi/v1/content/extract/69a7dac700cf95938f86d9bb" \
  -H "Authorization: Bearer $LISTENHUB_API_KEY" \
  -H "X-Source: skills"
  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" \
  -H "X-Source: skills" \
  -d '{
    "source": {
      "type": "url",
      "uri": "https://x.com/elonmusk"
    },
    "options": {
      "twitter": {
        "count": 50
      }
    }
  }'
  1. Poll until complete, present results.

平台分布

Codex

34.46%
按下载量换算1,882

Claude

29.01%
按下载量换算1,585

Cursor

18.66%
按下载量换算1,019

Gemini CLI

9.96%
按下载量换算544

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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