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 calesthio/generative-media-skills --skill audiobook-productiongit clone --depth 1 https://github.com/calesthio/generative-media-skillsWrote 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/calesthio/generative-media-skills/audiobook-production)<a href="https://agentmods.dev/skills/calesthio/generative-media-skills/audiobook-production"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/audiobook-production/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/calesthio/generative-media-skills/audiobook-production"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/audiobook-production.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 379 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00143 | $0.08020 |
| Opus 5 | $0.00072 | $0.04010 |
| Sonnet 5 | $0.00029 | $0.01604 |
| Haiku 4.5 | $0.00014 | $0.00802 |
Grade A, and why
audiobook-production 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 13d 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 — 570 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audiobook production
An audiobook is not a long TTS clip. It is a structured deliverable of many chapterized files, each of which must pass an automated loudness/noise gate, carry the right metadata, and sound like the same performer that opened Chapter
- The problems that dominate this work — voice drift over ten hours, a proper noun mispronounced 40 times, a footnote that makes no sense read aloud, a file rejected for a -58 dB noise floor, a platform that silently bans AI narration — do not exist in short-clip synthesis. This skill is about managing hour-scale production, not about generating one good sentence.
This is a craft skill, provider-neutral. Generative voice tools are referenced by capability (pronunciation lexicon, SSML support, seed/consistency control, per-chapter regeneration), not by brand. Specific tools and retail platforms are named only as illustrative examples or as dated policy facts.
Labels used below:
- [Fact] — documented in a primary/official source, cited.
- [Standard] — an established industry technical standard.
- [Heuristic] — a production judgment that experienced producers use; not a rule.
- [Policy — dated] — a volatile platform policy verified on the stated date.
1. Decide the production route first
Three routes exist, and they diverge on cost, rights, quality ceiling, and where you can sell. Pick before touching the manuscript, because the route changes how you prepare it.
- Human narration — a person performs the book. Highest quality ceiling, required by some retailers, needs a performer and studio-grade audio.
- Author/producer-driven generative narration — you supply the text to a TTS system, tune pronunciation and pacing, and master the output yourself. You control every file and can distribute the finished audio wide.
- Platform auto-narration — a retailer generates the audiobook from your ebook inside their walled system (e.g., Amazon's Virtual Voice, Google Play Books auto-narration, Apple Books digital narration). Lowest effort, least control, and distribution is often tied to that platform.
What ships with it
1 file 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.
- 13d ago First seen · 570 lines · 143 tokens per session scan A 61c7140b20fb
audiobook-production is a skill published in the GitHub repository calesthio/generative-media-skills (170 stars, last pushed 2mo ago), licensed MIT. It adds 143 tokens to every session and 8,020 once invoked, about $0.0007 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.
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cliptalk-social-reframe-exporter
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