Video Podcast Maker Lite
Agents365-ai/video-podcast-maker
Minimal personal narrated-video pipeline — a topic becomes a talking-head-free explainer MP4 (1080p or 4K) via script → Azure TTS (SSML) → Remotion.
Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns.
Install Azure Face
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MicrosoftDocs/Agent-Skills azure-face --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/azure-face .claude/skills/azure-face && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .claude/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-faceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MicrosoftDocs/Agent-Skills azure-face --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/azure-face .agents/skills/azure-face && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .agents/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MicrosoftDocs/Agent-Skills azure-face --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/azure-face .cursor/skills/azure-face && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .cursor/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MicrosoftDocs/Agent-Skills.git --path skills/azure-face--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MicrosoftDocs/Agent-Skills azure-face --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/azure-face .gemini/skills/azure-face && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .gemini/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MicrosoftDocs/Agent-Skills azure-faceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/azure-face .github/skills/azure-face && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .github/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MicrosoftDocs/Agent-Skills azure-face --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/azure-face .opencode/skills/azure-face && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-face" agent skill from https://github.com/MicrosoftDocs/Agent-Skills/tree/main/skills/azure-face into .opencode/skills/azure-face/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-face", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
azure-face- GitHub stars
- 775
- Token cost
- ~1.5k tokens
- SKILL.md length
- 442 words
- Files
- 1
- Skills in repo
- 149
- Repo updated
- First seen
- Licence
- CC-BY-4.0
At a glance
Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns.
- Using Face detection
- SKILL.md covers How to Use This Skill and Category Index
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- PersonGroup/Directory
What it does
Azure Face is an agent skill from MicrosoftDocs/Agent-Skills, published by the product's own GitHub organization. Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Use when using Face detection, identification, verification, liveness, PersonGroup/Directory, or Face API quotas, and other Azure AI Face related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use…
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires network access. Uses mcpmicrosoftdocs:microsoftdocsfetch or fetchwebpage to retrieve documentation.
It sits in Media & Creative, covering AI video generation. It works with Microsoft Azure, Azure AI Document Intelligence and Azure AI Vision. The repository describes itself as: Curated Agent Skills for Microsoft & Azure – giving AI coding assistants structured, real-time expertise from Microsoft Learn docs. The licence is CC-BY-4.0.
When your agent uses it
- Using Face detection
- PersonGroup/Directory
- Face API quotas
- Other Azure AI Face related development tasks
Example prompts
- “/azure-face”
Requirements
- Compatibility (from SKILL.md): Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
What it can do on your machine
Read from SKILL.md and the folder at commit ba74e8f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
learn.microsoft.comgithub.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
From compatibility in the SKILL.md frontmatter.
Context cost
Azure Face loads about 1.5k tokens when it runs. Until then it costs about 140 tokens; SKILL.md has 442 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from MicrosoftDocs/Agent-Skills at commit ba74e8f, republished under its CC-BY-4.0 licence (© MicrosoftDocs). 442 words, ~1,503 tokens.
Download SKILL.mdSave it as
.claude/skills/azure-face/SKILL.md (or your agent's skills folder).- name
- azure-face
- description
- Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Use when using Face detection, identification, verification, liveness, PersonGroup/Directory, or Face API quotas, and other Azure AI Face related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence).
- compatibility
- Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
- metadata.generated_at
- 2026-08-09
- metadata.generator
- docs2skills/1.0.0
Azure AI Face Skill
This skill provides expert guidance for Azure AI Face. Covers troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
- Preferred: Use
mcp_microsoftdocs:microsoft_docs_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L34-L38 | Diagnosing and fixing Azure Face API failures by interpreting error codes, understanding causes (quota, auth, input issues), and applying recommended resolutions. |
| Best Practices | L39-L47 | Guidance on enrolling faces, scaling PersonGroup/PersonDirectory, optimizing performance/latency, and building consent-aware, high-capacity Azure Face enrollment workflows. |
| Decision Making | L48-L53 | Guidance on choosing, configuring, and tuning Azure Face detection and recognition models, including model types, capabilities, parameters, and selection trade-offs. |
| Limits & Quotas | L54-L59 | Scaling PersonGroup for large face datasets and understanding Face API quotas, rate limits, and maximum sizes for persons, faces, and training operations. |
| Security | L60-L69 | Security and compliance for Face and liveness: abuse monitoring, token-based access control, network isolation, encryption/CMK, shared responsibility, and secure SDK version management. |
| Integrations & Coding Patterns | L70-L73 | How to call Azure Face API endpoints, use key operations (detect, identify, verify, find similar), and structure requests/responses in your applications. |
Show full SKILL.md (157 more words)Show less
Troubleshooting
| Topic | URL |
|---|---|
| Resolve Azure Face API errors using error codes | https://learn.microsoft.com/en-us/azure/ai-services/face/reference-face-error-codes |
Best Practices
| Topic | URL |
|---|---|
| Apply best practices for Azure Face enrollment | https://learn.microsoft.com/en-us/azure/ai-services/face/enrollment-overview |
| Add many faces to PersonGroup efficiently | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/add-faces |
| Optimize Azure Face performance and reduce latency | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/mitigate-latency |
| Use PersonDirectory for high-capacity face storage | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/use-persondirectory |
| Implement consent-focused Face enrollment app | https://learn.microsoft.com/en-us/azure/ai-services/face/tutorials/build-enrollment-app |
Decision Making
| Topic | URL |
|---|---|
| Choose and specify Azure Face detection models | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/specify-detection-model |
| Select and configure Azure Face recognition models | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/specify-recognition-model |
Limits & Quotas
| Topic | URL |
|---|---|
| Scale PersonGroup objects to large Face datasets | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/use-large-scale |
| Review Azure Face service quotas and limits | https://learn.microsoft.com/en-us/azure/ai-services/face/identity-quotas-limits |
Security
| Topic | URL |
|---|---|
| Configure abuse monitoring for Face liveness detection | https://learn.microsoft.com/en-us/azure/ai-services/face/concept-liveness-abuse-monitoring |
| Manage Face API access with limited tokens | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/identity-access-token |
| Use Face liveness detection with network isolation | https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/liveness-use-network-isolation |
| Configure encryption and CMK for Azure Face data | https://learn.microsoft.com/en-us/azure/ai-services/face/identity-encrypt-data-at-rest |
| Secure Face liveness solutions with shared responsibility | https://learn.microsoft.com/en-us/azure/ai-services/face/liveness-detection-shared-responsibility |
| Manage liveness client SDK versions for security | https://learn.microsoft.com/en-us/azure/ai-services/face/sdk/understand-the-liveness-sdk-versions |
Integrations & Coding Patterns
| Topic | URL |
|---|---|
| Use Azure Face API endpoints and operations | https://learn.microsoft.com/en-us/azure/ai-services/face/identity-api-reference |
© MicrosoftDocs, CC-BY-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/azure-face of MicrosoftDocs/Agent-Skills.
Open the folder on GitHubat commit ba74e8f
Compare with similar skills
Azure Face next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure Face this skillMicrosoftDocs/Agent-Skills | 775 | — | ~1.5k | Automated safety check: Pass | CC-BY-4.0 | |
| Video Podcast Maker LiteAgents365-ai/video-podcast-maker | 1.7k | — | ~4.5k | Automated safety check: Pass | MIT | |
| Azure AImicrosoft/GitHub-Copilot-for-Azure | 255 | 2 repos | ~852 | Automated safety check: Pass | MIT | |
| Azure AI Vision Imageanalysis Pymicrosoft/skills | 3.1k | 6 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Azure AI Document Intelligence Dotnetmicrosoft/skills | 3.1k | 6 repos | ~3k | Automated safety check: Pass | MIT | |
| Azure AI Document Intelligence TSmicrosoft/skills | 3.1k | 6 repos | ~2.4k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Azure Face
What does Azure Face do?
Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Azure Face is an agent skill from MicrosoftDocs/Agent-Skills, published by the product's own GitHub organization. Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns.
When should I use Azure Face?
Azure Face fits situations like: using Face detection; personGroup/Directory; face API quotas; other Azure AI Face related development tasks.
How do I install Azure Face in Claude Code?
Run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a claude-code`. Or copy the skill folder (skills/azure-face in MicrosoftDocs/Agent-Skills) into .claude/skills/azure-face in your project. Claude Code loads it when a task matches its description.
How do I install Azure Face in Codex?
Run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a codex`. Or copy the skill folder (skills/azure-face in MicrosoftDocs/Agent-Skills) into .agents/skills/azure-face in your project. Codex loads it when a task matches its description.
Can I use Azure Face in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-face -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-face, .gemini/skills/azure-face, .github/skills/azure-face and .opencode/skills/azure-face in your project.
What does Azure Face need to run?
SKILL.md names no scripts, command-line tools or credentials: Azure Face is instructions for the agent only. Compatibility (from SKILL.md): Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation..
Does Azure Face access the network?
SKILL.md names 2 domains. As links in the text: learn.microsoft.com and github.com. This is read from the text; nothing was executed.
Is Azure Face safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Azure Face use?
Azure Face is published under the CC-BY-4.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Azure Face use?
About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Azure Face?
Skills that share tags, products or a category with Azure Face: Video Podcast Maker Lite (Agents365-ai/video-podcast-maker, 1.7k stars), Azure AI (microsoft/GitHub-Copilot-for-Azure, 255 stars), Azure AI Vision Imageanalysis Py (microsoft/skills, 3.1k stars) and Azure AI Document Intelligence Dotnet (microsoft/skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Azure Face?
MicrosoftDocs (a GitHub organization, an official publisher) maintains it in MicrosoftDocs/Agent-Skills, which has 775 GitHub stars. The repository holds 149 skills in this directory. The repository was last updated on October 5, 2026.
Source: MicrosoftDocs/Agent-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.