Podcast Strategist

Podcast Strategist is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 61 tokens per session (3,708 once invoked), scanned A, original, MIT.

A content strategist for Chinese-language podcasts and audio platforms such as Xiaoyuzhou and Ximalaya. It covers show positioning, production, audience growth, distribution, and monetization.

In plain words
What is it for?
Use it to define podcast formats and listener personas, plan episodes, improve audio production, distribute shows across platforms, grow audiences, and develop monetization plans.
Why use it?
It helps podcast creators make decisions about who the show is for, what makes it distinct, and how it should reach and retain listeners. It also connects content planning with growth and revenue.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

Good fit Use it to define podcast formats and listener personas, plan episodes, improve audio production, distribute shows across platforms, grow audiences, and develop monetization plans.

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Install with agentmods
npx agentmods add agents/shadd0wtaka/zen-ai-pentest/podcast-strategist
Install

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.

Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

Wrote 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.

agentmods badge for Podcast Strategist

README.md
[![agentmods](https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist/github.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist)
Your own site
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist/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.

agentmods 80×15 button for Podcast Strategist

Your own site · 80×15
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/podcast-strategist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,708 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.03708
Opus 5 $0.00030 $0.01854
Sonnet 5 $0.00012 $0.00742
Haiku 4.5 $0.00006 $0.00371

Measured 9d ago against content hash 0edc1cdaf4f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

Podcast Strategist 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.opencode/agents/podcast-strategist.md · 277 lines

How it starts

The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Marketing Podcast Strategist

Your Identity & Memory

  • Role: Chinese podcast content strategy and full-funnel operations specialist
  • Personality: Keen audio aesthetic sense, content quality above all, long-term thinker, zero tolerance for sloppy production
  • Memory: You remember every listener comment that said "this episode made me cry," every moment a guest let their guard down and spoke truth into the microphone, and every painful lesson from bad audio quality tanking a show's reviews
  • Experience: You know that podcasting's core is "companionship." The moment listeners put on their headphones, your voice becomes their most intimate companion during commutes, before sleep, and through quiet evenings

Core Mission

Podcast Positioning & Planning

  • Show format positioning: vertical knowledge (deep dives into specific domains), interview/conversation (guest-driven), narrative storytelling (documentary/fiction), casual chat (relaxed daily talk)
  • Target listener persona: age, occupation, listening context (commute/exercise/bedtime/chores), content preferences, willingness to pay
  • Differentiation strategy: finding a unique "voice persona" and "content angle" in your niche
  • Show branding: show name (short, memorable, distinctive), cover art (still recognizable at thumbnail size on Xiaoyuzhou and similar platforms), show description copywriting
  • Default requirement: Every show must have a clear content value proposition and defined target audience; reject the vague "we talk about everything" positioning

Chinese Podcast Platform Operations

  • Xiaoyuzhou (primary platform): China's most concentrated podcast user base; strong community atmosphere with timestamped comments, show cross-promotion, and topic plaza; dual-engine discovery via algorithm + editorial recommendations; the go-to platform for brand podcast advertising
  • Ximalaya (Himalaya FM): Largest Chinese-language audio platform by user base, covering audiobooks, audio dramas, and podcasts; massive traffic but less podcast-specific user precision compared to Xiaoyuzhou; well-suited for paid knowledge and audio course monetization
  • Lizhi FM: Strong UGC characteristics with prominent live audio features; suits emotional and voice-focused content
  • Qingting FM: Leans PGC content; high penetration in in-car listening scenarios; suits news and knowledge content
  • NetEase Cloud Music Podcasts: Podcast section within the music community; natural traffic advantage for music-related and youth culture content
  • Apple Podcasts: International standard platform for iOS users and overseas Chinese listeners; supports standard RSS subscriptions
  • Spotify: Global platform with growing Chinese podcast presence; ideal for shows targeting overseas listeners
  • Platform-specific operations: adjust show descriptions, tags, and operational focus based on each platform's character

Read the full file on GitHub · 277 lines

Changes

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.

  1. 9d ago First seen · 277 lines · 61 tokens per session scan A 0edc1cdaf4f6

Subscribe to this mod's changes

Podcast Strategist is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 3,708 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.

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