Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rediumvex/ai-video-generator-claude --skill 10-podcast-visualgit clone --depth 1 https://github.com/rediumvex/ai-video-generator-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rediumvex/ai-video-generator-claude/10-podcast-visual)<a href="https://agentmods.dev/skills/rediumvex/ai-video-generator-claude/10-podcast-visual"><img src="https://agentmods.dev/badge/skills/rediumvex/ai-video-generator-claude/10-podcast-visual/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rediumvex/ai-video-generator-claude/10-podcast-visual"><img src="https://agentmods.dev/badge/skills/rediumvex/ai-video-generator-claude/10-podcast-visual.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.05768 |
| Opus 5 | $0.00045 | $0.02884 |
| Sonnet 5 | $0.00018 | $0.01154 |
| Haiku 4.5 | $0.00009 | $0.00577 |
Grade A, and why
seedance-podcast-visual scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Podcast Visual — Audio-to-Video Transformation Prompts
Transform podcast audio into cinematic visual content using Seedance 2.0 on Higgsfield. This skill produces video prompts that replace static audiograms with storytelling-driven visual experiences built entirely from constructed imagery.
Input Specifications
Primary inputs:
- Up to 3 audio files (podcast clips, interview excerpts, sound bites, episode highlights)
- Transcript or key quote text from the audio
- Speaker name(s) and brief context (topic, show name, tone)
- Desired visual style (abstract, cinematic, interview reconstruction, kinetic)
- Target platform (Instagram Reels, YouTube Shorts, LinkedIn, TikTok)
- Aspect ratio: 9:16 (vertical/mobile-first), 16:9 (widescreen), or 1:1 (square)
Audio file handling:
- File 1: Primary clip — the main sound bite or key quote being visualized
- File 2 (optional): Intro or context clip — sets up the narrative before the hook
- File 3 (optional): Reaction or follow-up clip — speaker response, co-host moment, audience reaction
- Duration guidance: each clip should be 15–90 seconds; total sequence up to 3 minutes
What you extract from audio before writing prompts:
- The single most quotable sentence (becomes the visual anchor)
- The emotional register: contemplative, fired-up, vulnerable, instructive, funny
- Pacing: fast and punchy vs. slow and deliberate delivery
- Natural pauses: where silence lives (these become visual breath moments)
- Speaker energy level: seated calm, animated gesturing, emotional peak
Philosophy
| Old model (audiogram) | New model (podcast visual) |
|---|---|
| Show the waveform | Show what the words feel like |
| Static background image | Constructed cinematic environment |
| Speaker photo as thumbnail | Speaker reconstructed in scene |
| Generic brand colors | Lighting and atmosphere matched to tone |
| Passive viewing | Active emotional engagement |
| Optimized for "audio on" | Compelling even on mute |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 367 lines · 90 tokens per session scan A 62a8cf049983
seedance-podcast-visual is a skill published in the GitHub repository rediumvex/ai-video-generator-claude (361 stars, last pushed 1mo ago), licensed MIT. It adds 90 tokens to every session and 5,768 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
linkedin-humanizer
Remove the AI tells human readers and LinkedIn's AI-slop filter react to in a post or comment: 2026 vocabulary by paragraph density, reveal bridges, staccato fragments, stacked triads, performed sincerity. Tiered rewriter (forensic / strict / aesthetic / all) plus --mode audit pass-fail review and --mode profile voice…
linkedin-marketing
Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the…
linkedin-reply-handler
Draft a reply to a specific existing LinkedIn comment from its URL. Use when the user wants to reply to a comment on any post, or follow up after an author replied to them. Parses the commentUrn, resolves the correct parentComment target (LinkedIn flattens threads to 2 levels), and posts via Publora on approval. Not…
linkedin-post-writer
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via…
linkedin-comment-drafter
Draft a LinkedIn comment on someone else's post from its URL, or reshare (repost) it to your feed with optional commentary. Use when the user pastes a post URL and asks to comment, engage, be first commenter, or repost with their thoughts. Produces 1-3 variants in the user's voice, picks a reaction, and publishes via…
linkedin-content-planner
Generate a 7-day LinkedIn content plan from a theme, audience, and pillars. Produces per-day post pillar, format, hook type, CTA, posting time, daily comment targets, and a weekly inbound-readiness check. Use when the user wants to plan a week or month of content, not draft a single post.