Azure Developer CLI (azd) is a command-line tool for building, deploying, and operating applications on Azure. Developers use it to move through application workflows such as coding, building, deployment, and monitoring with Azure templates and resources. Its catalogue entries help AI agents work with azd and Azure application projects.
Borrowing it
Nothing to install: this file belongs to Azure/azure-dev. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Azure/azure-dev/main/.github/skills/weekly-demo-video/SKILL.mdgit clone --depth 1 https://github.com/Azure/azure-devWrote 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/azure/azure-dev/weekly-demo-video)<a href="https://agentmods.dev/skills/azure/azure-dev/weekly-demo-video"><img src="https://agentmods.dev/badge/skills/azure/azure-dev/weekly-demo-video/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/azure/azure-dev/weekly-demo-video"><img src="https://agentmods.dev/badge/skills/azure/azure-dev/weekly-demo-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00135 | $0.00763 |
| Opus 5.5 | $0.00054 | $0.00305 |
| Sonnet 5.5 | $0.00027 | $0.00153 |
| Haiku 4.5 | $0.00014 | $0.00076 |
Grade A, and why
weekly-demo-video 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.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Demo Video Generator
Generates narrated MP4 demo videos for azd features using Python + Pillow + edge-tts + ffmpeg.
Prerequisites
Ensure these tools are installed:
| Tool | Purpose |
|---|---|
| Python 3 | Script execution |
| Pillow | Slide generation (pip install Pillow) |
| ffmpeg | Video/audio stitch |
| edge-tts | Neural TTS (pip install edge-tts) |
Verify prerequisites (bash):
python3 -c "from PIL import Image; print('ok')"
ffmpeg -version
edge-tts --list-voices > /dev/null
Execution Flow
Step 1: Pull latest
cd <repo-root> # the azure-dev repository root
git checkout main && git pull --rebase
Step 2: Find commits for the week
Replace the dates below with the actual week range:
git log --oneline --since="YYYY-MM-DD" --until="YYYY-MM-DD" --no-merges
Use the current week window (7 days). For sprint demos, use a 2-week window.
Step 3: Identify demo-worthy features
Group related commits. Skip: typos, CI fixes, test-only, deps bumps, docs-only. Look for: new commands, UX improvements, perf gains, new flags, agent features.
Use explore agents in parallel to research each feature group (give them specific commit SHAs).
Step 4: Confirm with user
Present a table of proposed demos. Ask user to confirm or adjust before generating.
Step 5: Generate videos
Follow the conventions strictly:
{{ references/CONVENTIONS.md }}
Step 6: Report
List generated videos with filenames and durations. Offer short descriptions for docs.
Error Handling
- edge-tts failure: Retry once. If it fails again, log the error and skip that slide's audio — notify the user.
- ffmpeg failure: Check the ffmpeg error output. Common issues: missing codec, invalid image path. Print the error and stop — don't produce a partial video.
- Font not found: Falls back to
ImageFont.load_default()automatically. Warn the user that slides may look different.
Output
All videos go to: <repo-root>/demo-video/
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.
- 1mo ago First seen · 99 lines · 135 tokens per session scan A 6d2b19f454a9
weekly-demo-video is a skill published in the GitHub repository Azure/azure-dev (570 stars, last pushed today), licensed MIT. It adds 135 tokens to every session and 763 once invoked, about $0.0005 per session on Opus 5.5. 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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