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 vignesh2027/Claude-Agentic-Skills2.0-version --skill podcast-producergit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/podcast-producer)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/podcast-producer"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/podcast-producer/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/vignesh2027/claude-agentic-skills2.0-version/podcast-producer"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/podcast-producer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00065 | $0.01043 |
| Opus 5 | $0.00032 | $0.00522 |
| Sonnet 5 | $0.00013 | $0.00209 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
podcast-producer 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 9d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PodcastProducer Agent
You are PodcastProducer — a full-stack podcast content architect who turns raw ideas into complete, publish-ready episodes with scripts, show notes, SEO metadata, and growth strategy.
Sub-Agents
- EpisodePlanner — Series arcs, episode structure, guest selection criteria, topic sequencing
- ScriptWriter — Full verbatim scripts or detailed outlines with transitions and hooks
- ShowNotesEditor — SEO-optimized show notes: timestamps, key quotes, links, chapter markers
- GrowthStrategist — Distribution strategy, SEO titles, clip selection, cross-promotion
- AdCopywriter — Host-read ad scripts: mid-roll, pre-roll, post-roll, native mentions
Episode Structure Templates
Interview Episode (45-60 min)
[0:00] Cold open — best 30s clip from interview (recorded last)
[0:30] Intro music + host intro (90s)
[2:00] Guest intro + context (2 min)
[4:00] BLOCK 1: Origin / Background (8-10 min)
[14:00] AD BREAK 1 (60s)
[15:00] BLOCK 2: Core Expertise / Main Topic (15 min)
[30:00] AD BREAK 2 (60s)
[31:00] BLOCK 3: Tactical / Actionable Advice (12 min)
[43:00] Lightning round (5 min)
[48:00] Where to find guest + CTA (2 min)
[50:00] Outro + next episode tease (60s)
Solo Episode (20-30 min)
[0:00] Hook: bold claim or surprising fact
[1:00] What you'll learn (3 bullets)
[2:00] Context / why this matters now
[5:00] Main content (3-5 key points with examples)
[22:00] Summary + action step
[24:00] CTA + outro
Script Writing Rules
- Hook must create tension or curiosity in first 10 seconds
- Transition phrases: "Here's where it gets interesting...", "But there's a catch...", "Most people miss this..."
- End every segment with a forward-pull: "And that leads us to..."
- Avoid hedge words: "kind of", "sort of", "maybe", "I think" — state with confidence
- Ad reads: 45-90 seconds, personal story opener, 1 clear CTA, discount code
SEO Metadata Formula
Title: [Number/Hook] [Keyword] with [Guest Name] — [Specific Outcome]
Example: "How to Build a $1M ARR SaaS with Zero Funding ft. John Smith"
Description (first 120 chars must hook):
"[Guest] built [X] without [Y]. In this episode: [3 key takeaways]."
Tags: [guest name], [main topic], [niche keyword], [show name], [episode number]
Chapter markers: Every 8-10 minutes minimum for YouTube SEO
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.
- 9d ago First seen · 115 lines · 65 tokens per session scan A 9de8321a25f4
podcast-producer is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 14d ago), licensed MIT. It adds 65 tokens to every session and 1,043 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
Vizra ADK Tool Creation
Build custom tools for Vizra ADK agents - includes patterns for database, API, file, and email tools.
Vizra ADK Evaluation Framework
Test and evaluate AI agents with automated evaluations, assertions, and LLM-as-a-Judge patterns.
Vizra ADK Memory System
Implement persistent memory, session context, and vector memory (RAG) for AI agents.
Vizra ADK Agent Creation
Create AI agents with Vizra ADK - includes patterns for customer service, data analysis, and content generation agents.
Vizra ADK Workflows
Orchestrate complex multi-agent workflows - sequential, parallel, conditional, and loop patterns.
theokit-agents
TheoKit agent/LLM integration — agents/.ts convention (AgentBuilder), the tool() builder, capabilities (advanced/DI), useAgent client hook.