Agent skill

Listenhub

by LeoYeAI in LeoYeAI/openclaw-master-skills

Explain anything — turn ideas into podcasts, explainer videos, or voice narration.

MITAuto-check passedMedia & Creative

Install Listenhub

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill listenhub -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills listenhub --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/listenhub .claude/skills/listenhub && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
listenhub
GitHub stars
2.2k
Token cost
~5.3k tokens
SKILL.md length
2,126 words
Files
13 (incl. scripts)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Explain anything — turn ideas into podcasts, explainer videos, or voice narration.

  • Works in 4 steps: Receive input + detect mode → Submit generation → Query status → …
  • The user wants to make a podcast
  • SKILL.md covers ⛔ Hard Constraints (Inviolable), Script Location, Private Data (Cannot Be… and Design Philosophy, plus 7 more sections
  • Runs Shell scripts from its folder; reaches listenhub.ai and youtube.com; needs LISTENHUB_API_KEY

What it does

Listenhub is an agent skill from LeoYeAI/openclaw-master-skills. Explain anything — turn ideas into podcasts, explainer videos, or voice narration. Use when the user wants to "make a podcast", "create an explainer video", "read this aloud", "generate an image", or share knowledge in audio/visual form. Supports: topic descriptions, YouTube links, article URLs, plain text, and image prompts.

Its SKILL.md is about 5.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts (for example `_meta.json`, `scripts/check-status.sh` and `scripts/create-explainer.sh`).

It sits in Media & Creative, covering Video production, Image generation and Podcasting. It works with YouTube. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • The user wants to make a podcast
  • Create an explainer video
  • Read this aloud
  • Generate an image

Example prompts

  • “make a podcast”
  • “create an explainer video”
  • “read this aloud”
  • “/listenhub”

Requirements

  • A Bash shell
  • A credential in LISTENHUB_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Receive input + detect mode
  2. Submit generation
  3. Query status
  4. Show results

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 11 files in scripts/ (Shell), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • listenhub.ai
    • youtube.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LISTENHUB_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Listenhub loads about 5.3k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 2,126 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~5.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 2,126 words, ~5,260 tokens.

Download SKILL.mdSave it as .claude/skills/listenhub/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.
name
listenhub
description
Explain anything — turn ideas into podcasts, explainer videos, or voice narration. Use when the user wants to "make a podcast", "create an explainer video", "read this aloud", "generate an image", or share knowledge in audio/visual form. Supports: topic descriptions, YouTube links, article URLs, plain text, and image prompts.
<purpose>
**The Hook**: Paste content, get audio/video/image. That simple.

Four modes, one entry point:

  • Podcast — Two-person dialogue, ideal for deep discussions
  • Explain — Single narrator + AI visuals, ideal for product intros
  • TTS/Flow Speech — Pure voice reading, ideal for articles
  • Image Generation — AI image creation, ideal for creative visualization

Users don't need to remember APIs, modes, or parameters. Just say what you want. </purpose>

<instructions>

⛔ Hard Constraints (Inviolable)

The scripts are the ONLY interface. Period.

┌─────────────────────────────────────────────────────────┐
│  AI Agent  ──▶  ./scripts/*.sh  ──▶  ListenHub API     │
│                      ▲                                  │
│                      │                                  │
│            This is the ONLY path.                       │
│            Direct API calls are FORBIDDEN.              │
└─────────────────────────────────────────────────────────┘

MUST:

  • Execute functionality ONLY through provided scripts in **/skills/listenhub/scripts/
  • Pass user intent as script arguments exactly as documented
  • Trust script outputs; do not second-guess internal logic

MUST NOT:

  • Write curl commands to ListenHub/Marswave API directly
  • Construct JSON bodies for API calls manually
  • Guess or fabricate speakerIds, endpoints, or API parameters
  • Assume API structure based on patterns or web searches
  • Hallucinate features not exposed by existing scripts

Why: The API is proprietary. Endpoints, parameters, and speakerIds are NOT publicly documented. Web searches will NOT find this information. Any attempt to bypass scripts will produce incorrect, non-functional code.

Script Location

Scripts are located at **/skills/listenhub/scripts/ relative to your working context.

Different AI clients use different dot-directories:

  • Claude Code: .claude/skills/listenhub/scripts/
  • Other clients: may vary (.cursor/, .windsurf/, etc.)

Resolution: Use glob pattern **/skills/listenhub/scripts/*.sh to locate scripts reliably, or resolve from the SKILL.md file's own path.

Private Data (Cannot Be Searched)

The following are internal implementation details that AI cannot reliably know:

CategoryExamplesHow to Obtain
API Base URLapi.marswave.ai/...✗ Cannot — internal to scripts
Endpointspodcast/episodes, etc.✗ Cannot — internal to scripts
Speaker IDscozy-man-english, etc.✓ Call get-speakers.sh
Request schemasJSON body structure✗ Cannot — internal to scripts
Response formatsEpisode ID, status codes✓ Documented per script

Rule: If information is not in this SKILL.md or retrievable via a script (like get-speakers.sh), assume you don't know it.

Design Philosophy

Hide complexity, reveal magic.

Users don't need to know: Episode IDs, API structure, polling mechanisms, credits, endpoint differences. Users only need: Say idea → wait a moment → get the link.

Environment

ListenHub API Key

API key stored in $LISTENHUB_API_KEY. Check on first use:

bash
source ~/.zshrc 2>/dev/null; [ -n "$LISTENHUB_API_KEY" ] && echo "ready" || echo "need_setup"

If setup needed, guide user:

  1. Visit https://listenhub.ai/settings/api-keys
  2. Paste key (only the lh_sk_... part)
  3. Auto-save to ~/.zshrc
Image Generation API Key

Image generation uses the same ListenHub API key stored in $LISTENHUB_API_KEY. Image generation output path defaults to the user downloads directory, stored in $LISTENHUB_OUTPUT_DIR.

On first image generation, the script auto-guides configuration:

  1. Visit https://listenhub.ai/settings/api-keys (requires subscription)
  2. Paste API key
  3. Configure output path (default: ~/Downloads)
  4. Auto-save to shell rc file

Security: Never expose full API keys in output.

Mode Detection

Auto-detect mode from user input:

→ Podcast (1-2 speakers) Supports single-speaker or dual-speaker podcasts. Debate mode requires 2 speakers. Default mode: quick unless explicitly requested. If speakers are not specified, call get-speakers.sh and select the first speakerId matching the chosen language. If reference materials are provided, pass them as --source-url or --source-text. When the user only provides a topic (e.g., "I want a podcast about X"), proceed with:

  1. detect language from user input,
  2. set mode=quick,
  3. choose one speaker via get-speakers.sh matching the language,
  4. create a single-speaker podcast without further clarification.
  1. Keywords: "podcast", "chat about", "discuss", "debate", "dialogue"
  2. Use case: Topic exploration, opinion exchange, deep analysis
  • Feature: Two voices, interactive feel

→ Explain (Explainer video)

  • Keywords: "explain", "introduce", "video", "explainer", "tutorial"
  • Use case: Product intro, concept explanation, tutorials
  • Feature: Single narrator + AI-generated visuals, can export video

→ TTS (Text-to-speech) TTS defaults to FlowSpeech direct for single-pass text or URL narration. Script arrays and multi-speaker dialogue belong to Speech as an advanced path, not the default TTS entry. Text-to-speech input is limited to 10,000 characters; split or use a URL when longer.

  1. Keywords: "read aloud", "convert to speech", "tts", "voice"
  2. Use case: Article to audio, note review, document narration
  3. Feature: Fastest (1-2 min), pure audio
Ambiguous "Convert to speech" Guidance

When the request is ambiguous (e.g., "convert to speech", "read aloud"), apply:

  1. Default to FlowSpeech and prioritize direct to avoid altering content.
  2. Input type: URL uses type=url, plain text uses type=text.
  3. Speaker: if not specified, call get-speakers and pick the first speakerId matching language.
  4. Switch to Speech only when multi-line scripts or multi-speaker dialogue is explicitly requested, and require scripts.

Example guidance:

“This request can use FlowSpeech with the default direct mode; switch to smart for grammar and punctuation fixes. For per-line speaker assignment, provide scripts and switch to Speech.”

→ Image Generation

  • Keywords: "generate image", "draw", "create picture", "visualize"
  • Use case: Creative visualization, concept art, illustrations
  • Feature: AI image generation via Labnana API, multiple resolutions and aspect ratios

Reference Images via Image Hosts When reference images are local files, upload to a known image host and use the direct image URL in --reference-images. Recommended hosts: imgbb.com, sm.ms, postimages.org, imgur.com. Direct image URLs should end with .jpg, .png, .webp, or .gif.

Default: If unclear, ask user which format they prefer.

Explicit override: User can say "make it a podcast" / "I want explainer video" / "just voice" / "generate image" to override auto-detection.

Interaction Flow

Step 1: Receive input + detect mode
→ Got it! Preparing...
  Mode: Two-person podcast
  Topic: Latest developments in Manus AI

For URLs, identify type:

  • youtu.be/XXX → convert to https://www.youtube.com/watch?v=XXX
  • Other URLs → use directly
Step 2: Submit generation
→ Generation submitted

  Estimated time:
  • Podcast: 2-3 minutes
  • Explain: 3-5 minutes
  • TTS: 1-2 minutes

  You can:
  • Wait and ask "done yet?"
  • Use check-status via scripts
  • View outputs in product pages:
    - Podcast: https://listenhub.ai/app/podcast
    - Explain: https://listenhub.ai/app/explainer
    - Text-to-Speech: https://listenhub.ai/app/text-to-speech
  • Do other things, ask later

Internally remember Episode ID for status queries.

Step 3: Query status

When user says "done yet?" / "ready?" / "check status":

  • Success: Show result + next options
  • Processing: "Still generating, wait another minute?"
  • Failed: "Generation failed, content might be unparseable. Try another?"
Step 4: Show results

Podcast result:

✓ Podcast generated!

  "{title}"

  Episode: https://listenhub.ai/app/episode/{episodeId}

  Duration: ~{duration} minutes

  Download audio: provide audioUrl or audioStreamUrl on request

One-stage podcast creation generates an online task. When status is success, the episode detail already includes scripts and audio URLs. Download uses the returned audioUrl or audioStreamUrl without a second create call. Two-stage creation is only for script review or manual edits before audio generation.

Explain result:

✓ Explainer video generated!

  "{title}"

  Watch: https://listenhub.ai/app/explainer

  Duration: ~{duration} minutes

  Need to download audio? Just say so.

Image result:

✓ Image generated!

  ~/Downloads/labnana-{timestamp}.jpg

Image results are file-only and not shown in the web UI.

Important: Prioritize web experience. Only provide download URLs when user explicitly requests.

Script Reference

Scripts are shell-based. Locate via **/skills/listenhub/scripts/. Dependency: jq is required for request construction. The AI must ensure curl and jq are installed before invoking scripts.

⚠️ Long-running Tasks: Generation may take 1-5 minutes. Use your CLI client's native background execution feature:

  • Claude Code: set run_in_background: true in Bash tool
  • Other CLIs: use built-in async/background job management if available

Invocation pattern:

bash
$SCRIPTS/script-name.sh [args]

Where $SCRIPTS = resolved path to **/skills/listenhub/scripts/

Podcast (One-Stage)

Default path. Use unless script review or manual editing is required.

bash
$SCRIPTS/create-podcast.sh --query "The future of AI development" --language en --mode deep --speakers cozy-man-english
$SCRIPTS/create-podcast.sh --query "Analyze this article" --language en --mode deep --speakers cozy-man-english --source-url "https://example.com/article"

Multiple --source-url and --source-text arguments are supported to combine several references in one request.

Podcast (Two-Stage: Text → Review → Audio)

Advanced path. Use only when script review or edits are explicitly requested.

The entire value of two-stage generation is human review between stages. Skipping review reduces it to one-stage with extra latency — never do this.

Stage 1: Generate text content.

bash
$SCRIPTS/create-podcast-text.sh --query "AI history" --language en --mode deep --speakers cozy-man-english,travel-girl-english

Review Gate (mandatory): After text generation completes, the agent MUST:

  1. Run check-status.sh --wait to poll until completion. On exit code 2 (timeout or rate-limited), wait briefly and retry.
  2. Save two files from the response:
    • ~/Downloads/podcast-draft-<episode-id>.md — human-readable version assembled from the response fields (title, outline, sourceProcessResult.content, and the scripts array formatted as readable dialogue). This is for the user to review.
    • ~/Downloads/podcast-scripts-<episode-id>.json — the raw {"scripts": [...]} object extracted from the response, exactly in the format that create-podcast-audio.sh --scripts expects. This is the machine-readable source of truth for Stage 2.
  3. Inform the user that both files have been saved, and offer to open the markdown draft for review (use the open command on macOS).
  4. STOP and wait for explicit user approval before proceeding to Stage 2.
  5. On user approval:
    • No changes: run create-podcast-audio.sh --episode <id> without --scripts (server uses original).
    • With edits: the user may edit the JSON file directly, or describe changes for the agent to apply. Pass the modified file via --scripts.

The agent MUST NOT proceed to Stage 2 automatically. This is a hard constraint, not a suggestion.

Stage 2: Generate audio from reviewed/approved text.

bash
# User approved without changes:
$SCRIPTS/create-podcast-audio.sh --episode "<episode-id>"

# User provided edits:
$SCRIPTS/create-podcast-audio.sh --episode "<episode-id>" --scripts modified-scripts.json
Show full SKILL.md (825 more words)Show less
Speech (Multi-Speaker)
bash
$SCRIPTS/create-speech.sh --scripts scripts.json
echo '{"scripts":[{"content":"Hello","speakerId":"cozy-man-english"}]}' | $SCRIPTS/create-speech.sh --scripts -

# scripts.json format:
# {
#   "scripts": [
#     {"content": "Script content here", "speakerId": "speaker-id"},
#     ...
#   ]
# }
Get Available Speakers
bash
$SCRIPTS/get-speakers.sh --language zh
$SCRIPTS/get-speakers.sh --language en

Guidance:

  1. 若用户未指定音色,必须先调用 get-speakers.sh 获取可用列表。
  2. 默认值兜底:取与 language 匹配的列表首个 speakerId 作为默认音色。

Response structure (for AI parsing):

json
{
  "code": 0,
  "data": {
    "items": [
      {
        "name": "Yuanye",
        "speakerId": "cozy-man-english",
        "gender": "male",
        "language": "zh"
      }
    ]
  }
}

Usage: When user requests specific voice characteristics (gender, style), call this script first to discover available speakerId values. NEVER hardcode or assume speakerIds.

Explain
bash
$SCRIPTS/create-explainer.sh --content "Introduce ListenHub" --language en --mode info --speakers cozy-man-english
$SCRIPTS/generate-video.sh --episode "<episode-id>"
TTS
bash
$SCRIPTS/create-tts.sh --type text --content "Welcome to ListenHub" --language en --mode smart --speakers cozy-man-english
Image Generation
bash
$SCRIPTS/generate-image.sh --prompt "sunset over mountains" --size 2K --ratio 16:9
$SCRIPTS/generate-image.sh --prompt "style reference" --reference-images "https://example.com/ref1.jpg,https://example.com/ref2.png"

Supported sizes: 1K | 2K | 4K (default: 2K). Supported aspect ratios: 16:9 | 1:1 | 9:16 | 2:3 | 3:2 | 3:4 | 4:3 | 21:9 (default: 16:9). Reference images: comma-separated URLs, maximum 14.

Check Status
bash
# Single-shot query
$SCRIPTS/check-status.sh --episode "<episode-id>" --type podcast

# Wait mode (recommended for automated polling)
$SCRIPTS/check-status.sh --episode "<episode-id>" --type podcast --wait
$SCRIPTS/check-status.sh --episode "<episode-id>" --type flow-speech --wait --timeout 60
$SCRIPTS/check-status.sh --episode "<episode-id>" --type explainer --wait --timeout 600

tts is accepted as an alias for flow-speech.

--wait mode handles polling internally with configurable limits. Agents SHOULD use --wait instead of manual polling loops. On exit code 2, wait briefly and retry the command.

OptionDefaultDescription
--waitoffEnable polling mode
--max-polls30Maximum poll attempts
--timeout300Maximum total wait (seconds)
--interval10Base poll interval (seconds)

Exit codes: 0 = completed, 1 = failed, 2 = timeout or rate-limited (still pending, safe to retry after a short wait).

Language Adaptation

Automatic Language Detection: Adapt output language based on user input and context.

Detection Rules:

  1. User Input Language: If user writes in Chinese, respond in Chinese. If user writes in English, respond in English.
  2. Context Consistency: Maintain the same language throughout the interaction unless user explicitly switches.
  3. CLAUDE.md Override: If project-level CLAUDE.md specifies a default language, respect it unless user input indicates otherwise.
  4. Mixed Input: If user mixes languages, prioritize the dominant language (>50% of content).

Application:

  • Status messages: "→ Got it! Preparing..." (English) vs "→ 收到!准备中..." (Chinese)
  • Error messages: Match user's language
  • Result summaries: Match user's language
  • Script outputs: Pass through as-is (scripts handle their own language)

Example:

User (Chinese): "生成一个关于 AI 的播客"
AI (Chinese): "→ 收到!准备双人播客..."

User (English): "Make a podcast about AI"
AI (English): "→ Got it! Preparing two-person podcast..."

Principle: Language is interface, not barrier. Adapt seamlessly to user's natural expression.

AI Responsibilities

Black Box Principle

You are a dispatcher, not an implementer.

Your job is to:

  1. Understand user intent (what do they want to create?)
  2. Select the correct script (which tool fits?)
  3. Format arguments correctly (what parameters?)
  4. Execute and relay results (what happened?)

Your job is NOT to:

  • Understand or modify script internals
  • Construct API calls directly
  • Guess parameters not documented here
  • Invent features that scripts don't expose
Mode-Specific Behavior

ListenHub modes (passthrough):

  • Podcast/Explain/TTS/Speech → pass user input directly
  • Server has full AI capability to process content
  • If user needs specific speakers → call get-speakers.sh first to list options

Labnana mode (passthrough by default):

  • Image Generation → pass the user's prompt through as-is by default
  • The generation model handles prompt interpretation; client-side rewriting is not required

Prompt Handling (Image Generation)

Default behavior: transparent forwarding. Pass the user's prompt directly to the script without modification.

When to offer optimization:

  • The user provides only a short topic or phrase (e.g., "a cat"), AND
  • The user has not explicitly stated they want verbatim generation

In this case, ask whether the user would like help enriching the prompt. Do not optimize without confirmation.

When to never modify:

  • The user pastes a long, structured, or detailed prompt — treat them as experienced
  • The user explicitly says "use this prompt exactly" or similar

If the user agrees to optimization, the following techniques are available as reference:

Style: "cyberpunk" → add "neon lights, futuristic, dystopian"; "ink painting" → add "Chinese ink painting, traditional art style"

Scene: time of day, lighting conditions, weather

Quality: "highly detailed", "8K quality", "cinematic composition"

Rules when optimizing:

  • Use English keywords (models trained on English)
  • Show the optimized prompt transparently before submitting
  • Keep the user's core intent unchanged
  • Do not over-stack terminology or add unwanted elements
</instructions>
<examples>
<example name="podcast-request">
<user>Make a podcast about the latest AI developments</user>
<response>
→ Got it! Preparing two-person podcast...
  Topic: Latest AI developments

→ Generation submitted, about 2-3 minutes

You can: • Wait and ask "done yet?" • Check listenhub.ai/app/library </response> </example>

<example name="explainer-request">
<user>Create an explainer video introducing Claude Code</user>
<response>
→ Got it! Preparing explainer video...
  Topic: Claude Code introduction

→ Generation submitted, explainer videos take 3-5 minutes

Includes: Script + narration + AI visuals </response> </example>

<example name="tts-request">
<user>Convert this article to speech https://blog.example.com/article</user>
<response>
→ Got it! Parsing article...

→ TTS submitted, about 1-2 minutes

Wait a moment, or ask "done yet?" to check </response> </example>

<example name="image-generation-short-prompt">
<user>Generate an image: cyberpunk city at night</user>
<response>
→ Short prompt detected. Would you like help enriching it with style/lighting/composition details, or use it as-is?
</response>
</example>
<example name="image-generation-detailed-prompt">
<user>Generate an image: "Cyberpunk city at night, neon lights reflecting on wet streets, towering skyscrapers with holographic ads, flying vehicles, cinematic composition, highly detailed, 8K quality"</user>
<response>
→ Generating image...

Prompt: Cyberpunk city at night, neon lights reflecting on wet streets, towering skyscrapers with holographic ads, flying vehicles, cinematic composition, highly detailed, 8K quality

Resolution: 2K (16:9)

✓ Image generated! ~/Downloads/labnana-20260121-143145.jpg </response> </example>

<example name="image-with-reference">
<user>Generate an image in this style: https://example.com/style-ref.jpg, prompt: "a futuristic car"</user>
<response>
→ Generating image with reference...

Prompt: a futuristic car Reference images: 1 Reference image URL: https://example.com/style-ref.jpg Resolution: 2K (16:9)

✓ Image generated! ~/Downloads/labnana-20260122-154230.jpg </response> </example>

<example name="status-check">
<user>Done yet?</user>
<response>
✓ Podcast generated!

"AI Revolution: From GPT to AGI"

Listen: https://listenhub.ai/app/podcast

Duration: ~8 minutes

Need to download? Just say so. </response> </example>

</examples>

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 12 other files (scripts) in skills/listenhub of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • scripts/check-status.sh
  • scripts/create-explainer.sh
  • scripts/create-podcast-audio.sh
  • scripts/create-podcast-text.sh
  • scripts/create-podcast.sh
  • scripts/create-speech.sh
  • scripts/create-tts.sh
  • scripts/generate-image.sh
  • scripts/generate-video.sh
  • scripts/get-speakers.sh
  • scripts/lib.sh

Open the folder on GitHubat commit e5199b5

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Works with

Questions about Listenhub

What does Listenhub do?

Explain anything — turn ideas into podcasts, explainer videos, or voice narration. Listenhub is an agent skill from LeoYeAI/openclaw-master-skills. Explain anything — turn ideas into podcasts, explainer videos, or voice narration.

When should I use Listenhub?

Listenhub fits situations like: the user wants to make a podcast; create an explainer video; read this aloud; generate an image.

How do I install Listenhub in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill listenhub -a claude-code`. Or copy the skill folder (skills/listenhub in LeoYeAI/openclaw-master-skills) into .claude/skills/listenhub in your project. Claude Code loads it when a task matches its description.

How do I install Listenhub in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill listenhub -a codex`. Or copy the skill folder (skills/listenhub in LeoYeAI/openclaw-master-skills) into .agents/skills/listenhub in your project. Codex loads it when a task matches its description.

Can I use Listenhub in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill listenhub -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/listenhub, .gemini/skills/listenhub, .github/skills/listenhub and .opencode/skills/listenhub in your project.

What does Listenhub need to run?

Going by SKILL.md and its folder, Listenhub needs a shell for the scripts in its folder and credentials named LISTENHUB_API_KEY. Our summary lists: A Bash shell; A credential in LISTENHUB_API_KEY.

Does Listenhub access the network?

SKILL.md names 2 domains. In commands or code: listenhub.ai and youtube.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Listenhub safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Listenhub use?

Listenhub is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Listenhub use?

About 5.3k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Listenhub?

Skills that share tags, products or a category with Listenhub: Media Gen (clacky-ai/openclacky, 1.2k stars), Youtube Thumbnail (hassancs91/claude-youtube-editor, 328 stars), Qwen Edit (digitalsamba/claude-code-video-toolkit, 2.2k stars) and Make Tsx (hassancs91/claude-youtube-editor, 328 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Listenhub?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.