podcast-pipeline
Podcast-to-Everything content pipeline. Takes a podcast RSS feed or raw transcript and generates a full cross-platform content calendar: short-form video clips, Twitter/X threads, LinkedIn articles, newsletter sections, quote cards, blog outlines with SEO keywords, and YouTube Shorts/TikTok scripts. Scores each piece by viral potential (novelty × controversy × utility) and deduplicates against recent output. Use when asked to: "repurpose this podcast", "turn this episode into content", "podcast content calendar", "extract clips from this episode", "podcast to social", "content from RSS feed", "batch process episodes", or any request to turn podcast/audio content into a multi-platform content plan.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow can fetch outsider-authored podcast content via RSS/URLs, then reads the resulting transcript text into the LLM context in `extract_content_atoms()` via `user_prompt` containing `transcript['text']` (and similarly derives atoms used in subsequent LLM calls), creating indirect prompt-injection exposure from outsider transcript content.
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The skill fetches RSS/audio content at runtime (e.g., "https://feeds.example.com/podcast.xml"), downloads/transcribes it, and directly injects the transcript into LLM prompts (extract_content_atoms → call_anthropic), so remote feed content can control model inputs.
- Repository
- ericosiu/ai-marketing-skills
- Commit
2eb0f34
- Audited
- Security analysis
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