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 azure-speechgit 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/azure-speech)<a href="https://agentmods.dev/skills/calesthio/generative-media-skills/azure-speech"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/azure-speech/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/azure-speech"><img src="https://agentmods.dev/badge/skills/calesthio/generative-media-skills/azure-speech.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, 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 228 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.
- medium Excessive Agency · line 246 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.
- medium Excessive Agency · line 405 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 | $0.00081 | $0.07849 |
| Opus 5 | $0.00041 | $0.03925 |
| Sonnet 5 | $0.00016 | $0.01570 |
| Haiku 4.5 | $0.00008 | $0.00785 |
Grade A, and why
azure-speech 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 8d 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 — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure Speech for media production agents
Use this skill when Azure Speech in Foundry Tools is a candidate provider for transcription, captions, subtitles, narration, synthetic voices, avatar speech, speech translation, video localization, or production speech QA.
Treat Azure Speech as a family of related services, not one model. Select the narrowest official capability that matches the job, then verify region, quota, language, pricing, and access status before committing.
Facts below were verified against Microsoft/Azure documentation on 2026-07-10. Volatile items such as supported locales, regions, pricing, quota values, API versions, and preview/limited-access status must be rechecked before paid or production use.
First decision: what job is the user actually asking for?
Documented facts:
- Azure Speech exposes speech to text, text to speech, speech translation, custom speech, custom voice, personal voice, text-to-speech avatar, video translation, LLM Speech, Speech SDK, Speech CLI, REST APIs, and containers in different combinations by region and access tier. Sources: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/overview and https://learn.microsoft.com/en-us/azure/ai-services/speech-service/regions
- Speech-to-text modes include real-time transcription, fast transcription, batch transcription, and custom speech. Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-to-text
- Text-to-speech modes include real-time synthesis, asynchronous batch synthesis for long-form audio, standard/prebuilt neural voices, HD voices, custom voice, personal voice, and avatar outputs. Sources: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/text-to-speech and https://learn.microsoft.com/en-us/azure/ai-services/speech-service/batch-synthesis
Production routing:
- Live captions, live dictation, live customer-support assist, or interactive voice UI → real-time speech to text through Speech SDK, Speech CLI, or real-time REST where supported.
- One prerecorded file where the editor needs quick transcript/subtitle timing → fast transcription API, if the file and region fit.
- Many prerecorded files, long back catalog, storage-based processing, diarization at scale, or custom speech model use → batch transcription.
- Narration, voiceover, accessibility read-aloud, or generated dialogue → text to speech with a selected standard/HD/custom/personal voice and SSML.
- Audiobook, long lesson, long article, or thousands of narration segments → batch synthesis; do not force real-time synthesis for long-form work.
- Source speech in one language with output text or spoken translation → speech translation or LLM Speech depending on latency, prompt-tuning, and output needs.
- Existing video localization with translated video output → video translation.
- Talking avatar driven by Azure Speech voice output → text-to-speech avatar. Use only when the avatar itself is part of the deliverable; otherwise generate audio and composite separately.
- Domain jargon or acoustic mismatch causing transcription errors → phrase list/custom speech evaluation, then custom speech training if the measured gain justifies it.
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.
- 8d ago First seen · 440 lines · 81 tokens per session scan A f51db9cb82c2
azure-speech is a skill published in the GitHub repository calesthio/generative-media-skills (170 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 7,849 once invoked, about $0.0004 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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