Podcast Production Pack

We built the Podcast Production Pack because we were exhausted by the fragmentation in audio distribution. You record a pristine interview, but the moment you hit export, you enter a black box of manual interventions. You're exporting WAVs, dragging them into a DAW, applying noise reduction by ear, and then manually crafting an RSS XML file. One missing attribute and your episode is rejected by Apple Podcasts. The ecosystem demands rich metadata—chapters, transcripts, alternate enclosures—but most creators treat these as afterthoughts. We wanted a workflow where the metadata is machine-readable, the audio processing is deterministic, and the distribution is validated before it leaves your machine. This skill gives you that pipeline.

The Post-Production Black Box and the RSS Trap

Treating podcast production like a content task rather than an engineering workflow is a trap. You end up with a zoo of error formats: some episodes are 96kHz stereo, others are 44.1kHz mono MP3s. Your RSS feed is a fragile artifact that breaks with every manual edit. We've seen engineers spend hours debugging XML schemas instead of focusing on the interview quality. The pain isn't just frustration; it's the risk of silent failures. An episode can sit in your feed with a broken itunes:duration tag, causing playback to fail on specific clients. Or worse, the audio drifts in loudness, causing listeners to bounce in the first 30 seconds because the mastering wasn't consistent.

If you're also pushing video, the Video Production Pack handles the dual-track workflow, but without a unified audio pipeline, you're managing two disjointed systems. We built this skill to unify the audio side, so you can treat your podcast like a CI/CD pipeline: deterministic, repeatable, and safe.

The Hidden Costs of Manual Audio Workflows

Ignoring this pipeline costs you more than just hours. Every manual edit introduces drift. You spend 3-4 hours per episode on post-production that should take minutes. You miss the growth window because you're stuck fixing XML schemas instead of marketing. Apple and Spotify reject episodes for minor namespace violations—like missing or malformed attributes. According to Podcasting 2.0 standards, the ecosystem is moving toward richer metadata, including transcripts and chapters, which drive discoverability ^[1]. If your feed doesn't support these, you're invisible to modern listeners and algorithms.

We've seen creators lose traction because their audio drifts in loudness, causing listeners to bounce in the first 30 seconds. The cost isn't just time; it's credibility. A broken RSS feed signals amateurism. A consistent, automated pipeline signals a brand. Plus, if you're pushing video, the Video Production Pack handles the dual-track workflow, but without a unified audio pipeline, you're managing two disjointed systems. We recommend pairing this with the Content Marketing Strategy Pack to turn episodes into multi-channel assets, ensuring the automation feeds your broader growth engine.

Automating the Episode Lifecycle with WDL and FFmpeg

Imagine a technical podcast team that publishes weekly. They record remote interviews and need to ship show notes, chapters, and transcripts for accessibility and SEO. Without automation, the host spends two days per episode: transcribing manually, finding timestamps, and crafting the RSS feed. They miss the window for the "New & Noteworthy" algorithm because they can't ship fast enough. The Podcasting 2.0 namespace solves this by allowing structured metadata like JSON chapters and transcript tags ^[6], ^[7]. A team using our workflow automates this. They run a WDL workflow that chains transcription, denoising, and metadata injection. The validate-rss-feed.sh script catches a missing tag before submission, preventing a rejection ^[8]. The result? The episode ships in 45 minutes with perfect audio standards and rich metadata, ready for distribution. This mirrors how engineering teams treat CI/CD for audio: deterministic, repeatable, and safe. We recommend pairing this with the Content Marketing Strategy Pack to turn episodes into multi-channel assets, ensuring the automation feeds your broader growth engine.

Sync your release dates with the Content Calendar Pack to maintain consistency, and use the output for a Product Launch Pack campaign. Repurpose long-form audio into a Online Course Creation Pack curriculum, or cross-post to audio platforms and manage clips via the YouTube Channel Pack and Social Media Strategy Pack. Drive traffic with the Blog Content Strategy Pack.

Deterministic Audio, Valid Feeds, and Rich Metadata

Once this skill is installed, your podcast workflow shifts from "hope it works" to "it ships." You get deterministic audio processing. The audio-mastering.sh script applies professional mastering using FFmpeg filters—afwtdn for noise reduction, adeclip for clipping, and aformat for sample rate normalization—so every episode hits the same loudness target. You never worry about codec drift again. The check-audio-standards.sh validator uses ffprobe to ensure your files meet distribution requirements, exiting non-zero if the sample rate or channel layout is wrong.

Your RSS feeds become rich with Podcasting 2.0 features: alternate enclosures for video companions ^[5], JSON chapters for web playback ^[6], and embedded transcripts ^[7]. You generate structured show notes automatically from JSON transcripts using generate-show-notes.py. The post-production.wdl orchestrates the entire chain, so you can focus on the interview, not the XML. Sync your release dates with the Content Calendar Pack to maintain consistency, and use the output for a Product Launch Pack campaign. Repurpose long-form audio into a Online Course Creation Pack curriculum, or cross-post to audio platforms and manage clips via the YouTube Channel Pack and Social Media Strategy Pack. Drive traffic with the Blog Content Strategy Pack.

What's in the Podcast Production Pack

• skill.md — Orchestrator skill that defines the end-to-end podcast production workflow, references all templates, scripts, validators, and reference docs, and provides usage instructions for AI agents.
• templates/post-production.wdl — Production-grade WDL workflow for automated podcast post-production. Chains tasks for transcription, denoising, mixing, mastering, and metadata generation using Context7 WDL patterns.
• scripts/audio-mastering.sh — Executable bash script that applies professional audio mastering using FFmpeg filters from Context7 (afwtdn, adeclip, amix, aformat, libfdk_aac) to prepare final episode files.
• references/ffmpeg-podcast-filters.md — Curated reference of FFmpeg audio filters relevant to podcasting, embedding canonical syntax and parameters for denoising, mixing, clipping removal, format negotiation, and transcription.
• references/wdl-automation-patterns.md — Curated reference of Workflow Description Language patterns for podcast automation, embedding canonical examples for task chaining, JSON I/O, string manipulation, and file operations.
• references/rss-distribution-standards.md — Curated reference of Apple Podcasts, IAB, and PSP RSS feed requirements, embedding canonical technical specifications, namespaces, and measurement guidelines for distribution.
• scripts/validate-rss-feed.sh — Executable validator script that checks an RSS feed XML against structural requirements (title, link, description, enclosure). Exits non-zero if standards are not met.
• scripts/generate-show-notes.py — Executable Python script that ingests a JSON transcript (simulating WDL output) and generates structured markdown show notes, timestamps, and key takeaways.
• validators/check-audio-standards.sh — Executable validator script that uses ffprobe to verify audio files meet podcast distribution standards (sample rate, channel layout, codec). Exits non-zero on failure.
• examples/episode-production-plan.md — Worked example demonstrating a complete episode lifecycle from ideation and guest coordination to recording, editing, hosting, and growth strategy execution.

Stop Hand-Editing XML. Ship on Autopilot.

Stop wrestling with DAW exports and manual RSS edits. Start shipping professional, metadata-rich episodes on autopilot. Upgrade to Pro to install the Podcast Production Pack and automate your entire workflow.