render-podcast-skit
Assemble a two-host fake-podcast skit ad from a config — per-line lipsync clips hard-concatenated in script order, scaled/padded to 1080×1920, WHITE bottom-center captions (up to 5 words per cue, broken on sentence punctuation, word-wrapped to stay in-frame, held at least 0.9s) built from each line's OWN ElevenLabs char-level timestamps (offset by cumulative clip start, never Whisper), and closed on a Playwright/PIL brand end card composited from the real wordmark — never AI-rendered text. This is the FREE deterministic assembly stage (concat + white captions + end card + crf28 encode); the per-line VOs, photoreal gpt-image-2 base stills, expression variants, and lipsync clips come from create-vo-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the podcast-skit format.
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Low
Low-risk findings worth noting
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tessl review fix ./skills/ads/capabilities/render-podcast-skit/SKILL.mdLow
Low-risk findings.
1 low severity finding. 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
In the required free assembly workflow (`stitch.py`), the agent ingests the VO-derived free-text content from the runtime-generated `scene-*.timestamps.json` (offset and grouped into caption cues), which ultimately comes from user-supplied `scenes[].text` submitted to ElevenLabs for with-timestamps.
- Repository
- gooseworks-ai/goose-skills
- Commit
8866b2a
- Audited
- Security analysis
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