HVE Core is a collection of agents, prompts, coding instructions, and skills for building repeatable software-development workflows with GitHub Copilot. It is intended for individuals and teams that want structured AI-assisted research, planning, implementation, and review, while the catalogue entries provide many of its reusable workflow components.
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 agentmods add skills/microsoft/hve-core/tts-voiceovernpx skills add microsoft/hve-core --skill tts-voiceovergit clone --depth 1 https://github.com/microsoft/hve-coreWrote 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/microsoft/hve-core/tts-voiceover)<a href="https://agentmods.dev/skills/microsoft/hve-core/tts-voiceover"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/tts-voiceover.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.01779 |
| Opus 5 | $0.00013 | $0.00890 |
| Sonnet 5 | $0.00005 | $0.00356 |
| Haiku 4.5 | $0.00003 | $0.00178 |
Grade A, and why
tts-voiceover 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 6d 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TTS Voice Over Skill
Generates per-slide WAV voice-over files from YAML speaker_notes using Azure Speech SDK with SSML pronunciation control.
Overview
This skill reads content.yaml files from a PowerPoint skill content directory, extracts speaker_notes fields, applies SSML acronym aliases for correct pronunciation of technical terms, and produces one WAV file per slide. Supports dry-run mode for SSML template verification without Azure credentials.
Prerequisites
- Azure Speech resource — Free tier provides 500K characters per month.
- Authentication — Key-based (
SPEECH_KEY) or Microsoft Entra ID (SPEECH_RESOURCE_ID). - Python 3.11+ with
uvfor virtual environment management. - Data handling note — Speaker-notes content is transmitted to the configured
SPEECH_REGIONfor synthesis. Operators must pin an approved region and avoid sending regulated or confidential narration.
Key-Based Auth
export SPEECH_KEY="your-speech-key"
export SPEECH_REGION="eastus"
Microsoft Entra ID Auth
Requires a custom domain on the Speech resource and Cognitive Services Speech User role.
export SPEECH_RESOURCE_ID="/subscriptions/.../Microsoft.CognitiveServices/accounts/your-resource"
export SPEECH_REGION="eastus"
Install dependencies:
# run from this skill folder
uv sync
Quick Start
Verify SSML templates without generating audio:
uv run scripts/generate_voiceover.py --dry-run --content-dir path/to/content
Generate voice-over WAV files:
uv run scripts/generate_voiceover.py --content-dir path/to/content --output-dir voice-over
Embed audio into a PPTX deck:
uv run scripts/embed_audio.py --input deck.pptx --audio-dir voice-over --output deck-narrated.pptx
Parameters Reference
generate_voiceover.py
| Parameter | Type | Default | Description |
|---|---|---|---|
--dry-run |
flag | false |
Print SSML templates without generating audio |
--voice |
string | en-US-Andrew:DragonHDLatestNeural |
Azure TTS voice name |
--rate |
string | +10% |
Speech prosody rate |
--content-dir |
path | content |
Path to slide content directory |
--output-dir |
path | voice-over |
Path to WAV output directory |
--lexicon |
path | (auto-detect) | Custom acronyms.yaml path |
--collapse-newlines |
flag | false |
Collapse newlines and whitespace runs in speaker notes into single spaces before synthesis |
--verbose / -v |
flag | false |
Enable verbose (DEBUG) logging output |
What ships with it
19 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.
- pip-audit-known-vulnerabilities.txt 260 B
- pyproject.toml 1.2 KB
- scripts/embed_audio.py 10 KB runs code
- scripts/embed-audio.sh 2.1 KB runs code
- scripts/generate_voiceover.py 16 KB runs code
- scripts/generate-voiceover.sh 2.5 KB runs code
- scripts/Invoke-EmbedAudio.ps1 2.5 KB runs code
- scripts/Invoke-GenerateVoiceover.ps1 3.1 KB runs code
- scripts/Modules/TtsVoiceoverHelpers.psm1 1.9 KB
- SECURITY.md 24 KB
- tests/corpus/0_acronym_text 19 B
- tests/corpus/0_empty 0 B
- tests/corpus/0_ssml_fragment 29 B
- tests/corpus/0_valid_yaml 25 B
- tests/fuzz_harness.py 6.0 KB runs code
- tests/test_embed_audio.py 6.1 KB runs code
- tests/test_generate_voiceover.py 8.4 KB runs code
- tests/TtsVoiceoverHelpers.Tests.ps1 4.9 KB runs code
- uv.lock 200 KB
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.
- 6d ago First seen · 196 lines · 25 tokens per session scan A 6bd0dabaac19
tts-voiceover is a skill published in the GitHub repository microsoft/hve-core (1,436 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,779 once invoked, about $0.0001 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…