Individual skill
podcast-production
Produce audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).
skills/production/content-formats/podcast-production/SKILL.md
Source commit 8c85352d5d75d4dcbe58480bd138e37b9742bab1
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- Observed behavior
- Instructions only
- Last checked
- Nov 11, 2026
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Repository context
- Repository stars (not skill ratings)
- 241
- Repository last updated
- Jul 14, 2026
- License
- MIT
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# Podcast production with generative tools
This skill covers producing a finished, publishable podcast episode when some or all of the
audio is machine-generated. It is provider-neutral: it names TTS engines, music libraries, and
hosts only as illustrative options, never as the method. The craft — format design, writing for
the ear, voice direction, structure, rights, loudness, delivery, disclosure, and QA — is the
same regardless of which tool renders the audio.
An episode is *done* when it (1) serves a defined show and audience, (2) sounds intentional and
consistent, (3) uses only audio you have the right to distribute, (4) meets the loudness and
file specs of its target platforms, (5) ships correct RSS metadata plus a transcript, (6)
carries any legally or platform-required AI disclosure, and (7) has passed a listen-through QA.
Skipping any of these is a defect, not a shortcut.
