How do I install the Render Podcast Skit skill?

Run npx skillmds add majiayu000/render-podcast-skit in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Render Podcast Skit safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Render Podcast Skit?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Render Podcast Skit free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Render Podcast Skit?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Render Podcast Skit by majiayu000 — Agent Skill

Name: Render Podcast Skit
Rating: 4.666666666666667 (3 reviews)
Author: majiayu000

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.

majiayu000 590d4c9 2 files · 6.0 KB Updated Sep 9, 2026 567 repo stars

File contents

render-podcast-skit

Assemble a two-host fake-podcast skit ad from a config: a skeptic and a believer at an absurd themed podcast desk do a snappy back-and-forth about the product (the set is deliberately unrelated — that is the joke). Each line is its own lipsync clip so the edit can cut on the dialogue beat (~1.8s avg); this capability is the FREE, deterministic assembly that concatenates those clips, renders the WHITE captions, and appends the brand end card.

scripts/config.example.json is the worked example (Ladder run-02 "Laundromat 2am", ~49s 1080×1920 9:16, ~22 lines); scripts/PIPELINE.md maps every config block to its source step and scripts/README.md documents the free assembly.

Run

This is the FREE, deterministic assembly stage — it spends nothing. The paid inputs are separate capabilities: one ElevenLabs with-timestamps VO per line (one voice per host) via create-vo-elevenlabs; two photoreal base stills at the themed desk plus ~10 expression variants (mouths NEUTRAL/CLOSED, gpt-image-2 quality=high, not nano-banana) via create-image-gpt-image-fal; and one lipsync clip per (still, VO) pair via create-video-fal. Given the per-line clips + their VO timestamps + the brand wordmark SVG, render-podcast-skit walks the scenes in script order, builds the global caption timeline, renders the WHITE captions, hard-concats the clips, auto-appends the end card, and final-encodes crf28 → the master. Re-cuts reuse the existing VOs / stills / clips and cost $0.

Contract (the free assembly)

Dialogue-carried, no music bed by default. The per-line VO is the audio; a podcast skit needs no music (an optional low ambience is a taste call, off by default).
One line = one scene = one hard cut, in script order. Hard-concat the per-line clips in order (scale/pad to 1080×1920, re-encode) — no dissolves.
Captions from the VO's OWN char-level timestamps, not Whisper (script-window). Build a global words.json by offsetting each line's char-level word timings by the cumulative clip start, group into ≤5-word cues broken on sentence-final punctuation, and render WHITE #FFFFFF bottom-center captions (black outline), word-wrapped to stay in-frame and held ≥0.9s — PIL PNG overlays when the host ffmpeg lacks libass (common), else ASS. (Yellow 3-word karaoke was the old style, rejected in testing.) Whisper on the rendered clips mistimes; the VO timestamps are ground truth.
End card via Playwright/PIL from the real wordmark — never AI-render brand text. The lockup is a deterministic HTML → PNG → 2.5s mp4 from the brand's real wordmark SVG (black bg, brand wordmark, CTA pill, URL), auto-appended after the last line. A diffusion model garbles a wordmark.
FFmpeg composite, deterministic, FREE. Concat the clips, overlay the WHITE caption PNGs (or burn ASS via libass), append the end-card mp4, and final-encode -preset slow -crf 28 + aac 96k → a 1080×1920 h264+aac master (~6MB for ~28s; the old -crf 20 produced ~16MB). No paid calls, no keys.

---name: render-podcast-skitdescription: 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.--- # render-podcast-skit Assemble a **two-host fake-podcast skit** ad from a config: a skeptic and a believer at an absurd themed podcast desk do a snappy back-and-forth about the product (the set is deliberately unrelated — that is the joke). Each line is its own lipsync clip so the edit can cut on the dialogue beat (~1.8s avg); this capability is the **FREE, deterministic assembly** that concatenates those clips, renders the WHITE captions, and appends the brand end card. `scripts/config.example.json` is the worked example (Ladder run-02 "Laundromat 2am", ~49s 1080×1920 9:16, ~22 lines); `scripts/PIPELINE.md` maps every config block to its source step and `scripts/README.md` documents the free assembly. ## Run This is the **FREE, deterministic** assembly stage — it spends nothing. The paid inputs are separate capabilities: one ElevenLabs **with-timestamps** VO per line (one voice per host) via `create-vo-elevenlabs`; two photoreal base stills at the themed desk plus ~10 expression variants (mouths NEUTRAL/CLOSED, **gpt-image-2 quality=high**, not nano-banana) via `create-image-gpt-image-fal`; and one lipsync clip per (still, VO) pair via `create-video-fal`. Given the per-line clips + their VO timestamps + the brand wordmark SVG, `render-podcast-skit` walks the scenes in script order, builds the global caption timeline, renders the WHITE captions, hard-concats the clips, auto-appends the end card, and final-encodes crf28 → the master. Re-cuts reuse the existing VOs / stills / clips and cost **$0**. ## Contract (the free assembly) - **Dialogue-carried, no music bed by default.** The per-line VO is the audio; a podcast skit needs no music (an optional low ambience is a taste call, off by default). - **One line = one scene = one hard cut, in script order.** Hard-concat the per-line clips in order (scale/pad to 1080×1920, re-encode) — no dissolves. - **Captions from the VO's OWN char-level timestamps, not Whisper (script-window).** Build a global `words.json` by offsetting each line's char-level word timings by the cumulative clip start, group into **≤5-word cues broken on sentence-final punctuation**, and render **WHITE `#FFFFFF`** bottom-center captions (black outline), **word-wrapped to stay in-frame** and held **≥0.9s** — PIL PNG overlays when the host ffmpeg lacks libass (common), else ASS. (Yellow 3-word karaoke was the old style, rejected in testing.) Whisper on the rendered clips mistimes; the VO timestamps are ground truth. - **End card via Playwright/PIL from the real wordmark — never AI-render brand text.** The lockup is a deterministic HTML → PNG → 2.5s mp4 from the brand's real wordmark SVG (black bg, brand wordmark, CTA pill, URL), auto-appended after the last line. A diffusion model garbles a wordmark. - **FFmpeg composite, deterministic, FREE.** Concat the clips, overlay the WHITE caption PNGs (or burn ASS via libass), append the end-card mp4, and **final-encode `-preset slow -crf 28` + aac 96k** → a 1080×1920 h264+aac master (~6MB for ~28s; the old `-crf 20` produced ~16MB). No paid calls, no keys.

Frequently asked questions