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Video Podcast Maker

v2.0.0

Use when user provides a topic and wants an automated video podcast created, OR when user wants to learn/analyze video design patterns from reference videos...

0· 67·0 current·0 all-time
byAgents365.ai@agents365-ai
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
Capability signals
CryptoRequires walletCan make purchasesRequires OAuth token
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
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Suspicious
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
Name/description, required binaries (python3, ffmpeg, node/npx) and code (Remotion templates, TTS backends, generation scripts) line up with a video podcast generator and design-learner. AZURE_SPEECH_KEY as the primary credential is appropriate for Azure TTS. The dependency on remotion-best-practices and use of Remotion/FFmpeg/TTS engines is coherent with the stated functionality.
Instruction Scope
SKILL.md instructs the agent to perform web research, TTS synthesis, Remotion rendering, frame extraction, and optional Playwright-based captures — all within expected scope. It also includes an auto-update routine that runs git fetch and (with explicit user consent) git pull in the skill directory and writes a .last_update_check timestamp file. Reading/writing files under ${CLAUDE_SKILL_DIR} and generating many project artifacts (timing.json, podcast_audio.wav, shorts/, etc.) is expected. No instructions request unrelated system secrets, but Playwright capture and the web-oriented parts may require additional binaries/permissions not declared in the metadata (browsers/Playwright).
Install Mechanism
Install spec uses brew to install ffmpeg (reasonable) and a 'uv' package entry for edge-tts (edge-tts is a known pip package). The 'uv' installer kind is ambiguous in the metadata (not a standard installer label), so it's unclear how edge-tts will be installed in the agent environment. The repository also contains an onyx_data/deployment README that shows a curl | install.sh pattern referencing raw.githubusercontent.com; that file is present in the repo but not automatically executed by SKILL.md. Presence of fetched-install instructions in the repo increases the attack surface if someone later runs those scripts, so treat them as a caution.
Credentials
The skill declares a single primary env var AZURE_SPEECH_KEY (appropriate for Azure TTS). The README and scripts reference many optional environment variables for other TTS backends (ELEVENLABS_API_KEY, OPENAI_API_KEY, VOLCENGINE_* etc.). Those are optional and reasonable for multi-backend TTS, but metadata only lists AZURE_SPEECH_KEY which is a mild inconsistency: the runtime may read additional env vars (if a user selects other backends) that aren't declared in requires.env. Users should be aware the skill will use any TTS-related keys present in their environment if configured to do so.
Persistence & Privilege
always:false (no forced/global install). The skill writes a .last_update_check timestamp in ${CLAUDE_SKILL_DIR} and contains an auto-update check that can run git fetch and — with explicit user confirmation — git pull to update code. This makes the skill able to modify its own code on disk with user consent. That behavior is documented in SKILL.md and prompts the user before pulling, but it increases runtime dynamism and should be considered when evaluating trustworthiness.
What to consider before installing
This skill appears to do what it claims (create video podcasts and learn visual design patterns), but there are a few things to watch before you install or run it: 1) Auto-update (git pull): The skill checks upstream and can pull updates into its own directory. It asks the user before pulling, but pulled updates change code that will later run on your machine — treat this like installing third‑party code on demand. Only allow updates if you trust the repository source. 2) Embedded deployment material: The repo contains an onyx_data/deployment README referencing a curl|install.sh flow (downloads a script from raw.githubusercontent.com). Those install instructions are present in the repo but are not automatically executed by the skill. Do NOT run those remote-install commands unless you review the script first. 3) Credentials/environment variables: The metadata declares AZURE_SPEECH_KEY as the primary credential, which is reasonable for Azure TTS. The README and code support many optional TTS backends (ElevenLabs, OpenAI, Volcengine, CosyVoice, Google). If you set those API keys in your environment, the skill may use them when configured — only provide keys you are comfortable sharing with this tool and consider using scoped keys. 4) Install ambiguity: The metadata lists an installer kind 'uv' for edge-tts — this is ambiguous. Confirm how edge-tts will be installed in your runtime (pip? other). Also, Playwright/browser capture is marked experimental and may require additional browser binaries; the SKILL.md does not declare those requirements explicitly. 5) Run in isolation: Because the skill runs arbitrary subprocesses (ffmpeg, npx remotion, ffprobe) and can modify files under its skill directory, run it in an isolated or disposable environment (container, VM, dedicated project directory) the first time. Inspect the code (especially any scripts that perform curl/downloads or execute external installers) before granting network access or API keys. 6) Verify remotion-best-practices dependency: The SKILL.md mandates invoking remotion-best-practices first. Confirm that skill’s source and trustworthiness, because this skill relies on it for core behavior. What would increase confidence: explicit installer steps that match typical package managers (pip/apt/brew) with no ambiguous 'uv' installer, explicit declaration of all optional env vars in metadata, and removal (or clearer documentation) of the onyx_data remote-install references. If you want, I can point out the specific files/lines that implement the auto-update, the curl references, and the code paths that read optional env vars so you can inspect them directly.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

Runtime requirements

🎬 Clawdis
OSmacOS · Linux
Binspython3, ffmpeg, node, npx
Primary envAZURE_SPEECH_KEY

Install

Homebrew
Bins: ffmpeg
brew install ffmpeg
uv
Bins: edge-tts
uv tool install edge-tts

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