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 archimedes-run/omniHarness --skill podcast-generationgit clone --depth 1 https://github.com/archimedes-run/omniHarnessWrote 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/archimedes-run/omniharness/podcast-generation)<a href="https://agentmods.dev/skills/archimedes-run/omniharness/podcast-generation"><img src="https://agentmods.dev/badge/skills/archimedes-run/omniharness/podcast-generation/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/archimedes-run/omniharness/podcast-generation"><img src="https://agentmods.dev/badge/skills/archimedes-run/omniharness/podcast-generation.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 | $0.00038 | $0.01620 |
| Opus 5.5 | $0.00015 | $0.00648 |
| Sonnet 5.5 | $0.00008 | $0.00324 |
| Haiku 4.5 | $0.00004 | $0.00162 |
Grade A, and why
podcast-generation 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 1mo 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.
This is a copy
88% identical to podcast-generation — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Podcast Generation Skill
Overview
This skill generates high-quality podcast audio from text content. The workflow includes creating a structured JSON script (conversational dialogue) and executing audio generation through text-to-speech synthesis.
Core Capabilities
- Convert any text content (articles, reports, documentation) into podcast scripts
- Generate natural two-host conversational dialogue (male and female hosts)
- Synthesize speech audio using text-to-speech
- Mix audio chunks into a final podcast MP3 file
- Support both English and Chinese content
Workflow
Step 1: Understand Requirements
When a user requests podcast generation, identify:
- Source content: The text/article/report to convert into a podcast
- Language: English or Chinese (based on content)
- Output location: Where to save the generated podcast
- You don't need to check the folder under
/mnt/user-data
Step 2: Create Structured Script JSON
Generate a structured JSON script file in /mnt/user-data/workspace/ with naming pattern: {descriptive-name}-script.json
The JSON structure:
{
"locale": "en",
"lines": [
{"speaker": "male", "paragraph": "dialogue text"},
{"speaker": "female", "paragraph": "dialogue text"}
]
}
Step 3: Execute Generation
Call the Python script:
python /mnt/skills/public/podcast-generation/scripts/generate.py \
--script-file /mnt/user-data/workspace/script-file.json \
--output-file /mnt/user-data/outputs/generated-podcast.mp3 \
--transcript-file /mnt/user-data/outputs/generated-podcast-transcript.md
Parameters:
--script-file: Absolute path to JSON script file (required)--output-file: Absolute path to output MP3 file (required)--transcript-file: Absolute path to output transcript markdown file (optional, but recommended)
[!IMPORTANT]
- Execute the script in one complete call. Do NOT split the workflow into separate steps.
- The script handles all TTS API calls and audio generation internally.
- Do NOT read the Python file, just call it with the parameters.
- Always include
--transcript-fileto generate a readable transcript for the user.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 186 lines · 38 tokens per session scan A c114f1425e93
podcast-generation is a skill published in the GitHub repository archimedes-run/omniHarness (7 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 1,620 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to podcast-generation, differing in 6 lines, and is treated as a copy.
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