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Agent Skill · 开发

explainer(explainer 搜索)

explainer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

explainer 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 2,589。

总安装 16,059周安装 656GitHub Stars 49下载 5,196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:explainer(explainer 搜索)
来源仓库:https://github.com/marswaveai/skills
仓库路径:skills/explainer
安装命令:
npx skills add https://github.com/marswaveai/skills --skill explainer
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 explainer

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。

explainer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前建议确认权限范围和维护状态,避免触发联网或文件读写操作。explainer 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/explainer

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 explainer;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

    它需要执行命令,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

explainer 怎么安装?

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

explainer 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。

explainer 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/marswaveai/skills --skill explainer 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

explainer 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。

explainer 用的人多吗?

公开数据是累计安装 16,059 次,近一周安装 656 次,下载 5,196 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。

explainer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
explainer

explainer 搜索 · 本页

16,05949执行命令未明确通过

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 wants to create an explainer or tutorial video
  • User asks to "explain" something in video form
  • User wants narrated content with AI-generated visuals
  • User says "explainer video", "解说视频", "tutorial video"

When NOT to Use

  • User wants audio-only content without visuals (use /speech or /podcast)
  • User wants a podcast-style discussion (use /podcast)
  • User wants to generate a standalone image (use /image-gen)
  • User wants to read text aloud without video (use /speech)

Purpose

Generate explainer videos that combine a single narrator's voiceover with AI-generated visuals. Ideal for product introductions, concept explanations, and tutorials. Supports text-only script generation or full text + video output.

Hard Constraints

  • Always read config following shared/config-pattern.md before any interaction
  • Follow shared/cli-patterns.md for execution modes, error handling, and interaction patterns
  • Always follow shared/cli-authentication.md for auth checks
  • Never hardcode speaker IDs — always fetch from the speakers CLI when the user wants to change voice
  • Never save files to ~/Downloads/ or .listenhub/ — save artifacts to the current working directory with friendly topic-based names (see shared/config-pattern.md § Artifact Naming)
  • Explainer uses exactly 1 speaker
  • Mode must be info (for Info style) or story (for Story style) — never slides (use /slides skill instead)

Step -1: CLI Auth Check

Follow shared/config-pattern.md § CLI Auth Check. If the CLI is not installed or the user is not logged in, auto-install and auto-login per shared/cli-authentication.md — never ask the user to run commands manually.

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/explainer"
echo '{"outputMode":"inline","language":null,"defaultStyle":null,"defaultSpeakers":{}}' > ".listenhub/explainer/config.json"
CONFIG_PATH=".listenhub/explainer/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/explainer/config.json"
[ ! -f "$CONFIG_PATH" ] && CONFIG_PATH="$HOME/.listenhub/explainer/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 (explainer):
  输出方式:{inline / download / both}
  语言偏好:{zh / en / 未设置}
  默认风格:{info / story / 未设置}
  默认主播:{speakerName / 使用内置默认}

Then ask:

  1. outputMode: Follow shared/output-mode.md § Setup Flow Question.
  2. Language (optional): "默认语言?"

- "中文 (zh)" - "English (en)" - "每次手动选择" → keep null

  1. Style (optional): "默认风格?"

- "Info — 信息展示型" - "Story — 故事叙述型" - "每次手动选择" → keep null

After collecting answers, save immediately:

NEW_CONFIG=$(echo "$CONFIG" | jq --arg m "$OUTPUT_MODE" '. + {"outputMode": $m}')
echo "$NEW_CONFIG" > "$CONFIG_PATH"
CONFIG=$(cat "$CONFIG_PATH")

Interaction Flow

Step 1: Topic / Content

Free text input. Ask the user:

What would you like to explain or introduce?

Accept: topic description, text content, or concept to explain.

Step 2: Language

If config.language is set, pre-fill and show in summary — skip this question. Otherwise ask:

Question: "What language?"
Options:
  - "Chinese (zh)" — Content in Mandarin Chinese
  - "English (en)" — Content in English
  - "Japanese (ja)" — Content in Japanese

Step 3: Style

If config.defaultStyle is set, pre-fill and show in summary — skip this question. Otherwise ask:

Question: "What style of explainer?"
Options:
  - "Info" — Informational, factual presentation style
  - "Story" — Narrative, storytelling approach

Step 4: Speaker Selection

Follow shared/speaker-selection.md:

  • If config.defaultSpeakers.{language} is set → use saved speaker silently
  • If not set → use built-in default from shared/speaker-selection.md for the language
  • Show the speaker in the confirmation summary (Step 6) — user can change from there if desired
  • Only show the full speaker list if the user explicitly asks to change voice

Speaker query: see shared/cli-speakers.md for listing and filtering speakers.

Only 1 speaker is supported for explainer videos.

Step 5: Output Type

Question: "What output do you want?"
Options:
  - "Text script only" — Generate narration script, no video
  - "Text + Video" — Generate full explainer video with AI visuals

Step 6: Confirm & Generate

Summarize all choices:

Ready to generate explainer:

  Topic: {topic}
  Language: {language}
  Style: {info/story}
  Speaker: {speaker name}
  Output: {text only / text + video}

  Proceed?

Wait for explicit confirmation before running any CLI command.

Workflow

Run the CLI command with run_in_background: true and timeout: 660000. The CLI blocks until generation completes and returns the final result as JSON:

listenhub explainer create \
  --query "{topic}" \
  --mode {info|story} \
  --lang {en|zh|ja} \
  --speaker "{name}" \
  --speaker-id "{id}" \
  --timeout 600 \
  --json

If the command fails (non-zero exit), check stderr for error details. See shared/cli-patterns.md § Error Handling for exit codes and common errors.

Optional flags (add when applicable):

  • --source-url "{url}" — if the user provided a reference URL
  • --skip-audio — if text-only output (no video)
  • --image-size {2K|4K} — image resolution (default: 2K)
  • --aspect-ratio {16:9|9:16|1:1} — video aspect ratio (default: 16:9)
  • --style "{style}" — visual style for AI-generated images

Tell the user the task is submitted. When notified of completion, parse and present result:

Parse the CLI JSON output for key fields:

EPISODE_ID=$(echo "$RESULT" | jq -r '.episodeId')
AUDIO_URL=$(echo "$RESULT" | jq -r '.audioUrl // empty')
VIDEO_URL=$(echo "$RESULT" | jq -r '.videoUrl // empty')
CREDITS=$(echo "$RESULT" | jq -r '.credits // empty')

Read OUTPUT_MODE from config. Follow shared/output-mode.md for behavior.

If text-only output:

inline or both: Present the script inline.

Present:

解说脚本已生成!

「{title}」

在线查看:https://listenhub.ai/app/explainer/{episodeId}

download or both: Also save the script file. Generate a topic slug following shared/config-pattern.md § Artifact Naming.

  • Save as {slug}-explainer.md in cwd (dedup if exists)
  • Present the save path in addition to the above summary.

If text + video output:

inline or both: Display video URL and audio URL as clickable links.

Present:

解说视频已生成!

视频链接:{videoUrl}
音频链接:{audioUrl}
消耗积分:{credits}

download or both: Also save files. Generate a topic slug following shared/config-pattern.md § Artifact Naming.

  • Create {slug}-explainer/ folder (dedup if exists)
  • Write script.md inside
  • Download audio: listenhub download "{audioUrl}" -o "{slug}-explainer/audio.mp3"
  • Present: 已保存到当前目录: {slug}-explainer/ script.md audio.mp3

After Successful Generation

Update config with the choices made this session:

NEW_CONFIG=$(echo "$CONFIG" | jq \
  --arg lang "{language}" \
  --arg style "{info/story}" \
  --arg speakerId "{speakerId}" \
  '. + {"language": $lang, "defaultStyle": $style, "defaultSpeakers": (.defaultSpeakers + {($lang): [$speakerId]})}')
echo "$NEW_CONFIG" > "$CONFIG_PATH"

Estimated times:

  • Text script only: 2-3 minutes
  • Text + Video: 5-10 minutes

Resources

  • CLI authentication: shared/cli-authentication.md
  • CLI patterns: shared/cli-patterns.md
  • Speaker query: shared/cli-speakers.md
  • Speaker selection guide: shared/speaker-selection.md
  • Config pattern: shared/config-pattern.md
  • Output mode: shared/output-mode.md

Composability

  • Invokes: speakers CLI (for speaker selection); may invoke /speech for voiceover
  • Invoked by: content-planner (Phase 3)

Example

User: "Create an explainer video introducing Claude Code"

Agent workflow:

  1. Topic: "Claude Code introduction"
  2. Ask language → "English"
  3. Ask style → "Info"
  4. Use default speaker "Mars" (cozy-man-english)
  5. Ask output → "Text + Video"
# Run with run_in_background: true, timeout: 660000
listenhub explainer create \
  --query "Introduce Claude Code: what it is, key features, and how to get started" \
  --mode info \
  --lang en \
  --speaker "Mars" \
  --speaker-id "cozy-man-english" \
  --timeout 600 \
  --json

Parse result for episodeId, audioUrl, videoUrl, credits, and present to user.

平台分布

Codex

33.13%
按下载量换算1,721

Claude

32.14%
按下载量换算1,670

Cursor

18.5%
按下载量换算961

Gemini CLI

10.07%
按下载量换算523

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/marswaveai/skills --skill explainer 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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