Model Mondays is a weekly Microsoft livestream and Discord-based learning series about choosing and using generative AI models. Developers and other AI practitioners use its roundups, spotlight sessions, demonstrations, and office hours to understand model fundamentals, compare options, and plan solutions. The catalogue contains an instruction related to the series.
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.
git clone --depth 1 https://github.com/microsoft/model-mondaysWrote 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/commands/microsoft/model-mondays/blog-review-example)<a href="https://agentmods.dev/commands/microsoft/model-mondays/blog-review-example"><img src="https://agentmods.dev/badge/commands/microsoft/model-mondays/blog-review-example/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/commands/microsoft/model-mondays/blog-review-example"><img src="https://agentmods.dev/badge/commands/microsoft/model-mondays/blog-review-example.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.01505 |
| Opus 5.5 | $0.00000 | $0.00602 |
| Sonnet 5.5 | $0.00000 | $0.00301 |
| Haiku 4.5 | $0.00000 | $0.00151 |
Grade A, and why
blog-review-example 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 21d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog Post Review: 2025-09-15.md (S2E13 Model Mondays)
🔧 MCP Status
✅ MCP Configuration Active: Enhanced review capabilities enabled with Microsoft Learn documentation access and GitHub repository context.
✅ Present Elements
1. Title ✅
- Clear, engaging title: "Model Mondays S2E13: Open Source Models & Community AI"
- Includes season and episode reference (S2E13)
- Follows consistent naming convention
- Reflects episode content accurately
2. Blurb ✅
- Compelling opening paragraph that hooks the reader
- Clearly explains episode coverage (open source AI, demos, workflows)
- Mentions special guest Jeff Boudier from Hugging Face
- References the season finale context
- Good connection between open models, community, and Microsoft Foundry
3. Key Takeaways ✅
- Contains exactly 5 well-structured bullet points
- Each point captures important insights from the episode
- Actionable and memorable statements
- Covers different aspects: open source permanence, community innovation, transparency, deployment, and learning
4. About Model Mondays ✅
- Clear description of the series format
- Key CTAs included (Watch replays, Register for AMA, Recap AMAs)
- Links to main Model Mondays resources
- Encourages engagement and participation
5. Join The Community ✅
- Multiple ways to connect (Discord, Forum)
- Clear CTAs for community participation
- Proper engagement encouragement
❌ Missing or Incomplete Elements
1. Banner Post ❌
- MISSING: No banner image included in the blog post
- The episode announcement shows there is a banner image available:
S2-E13.png - Should include proper image formatting and alt text
- Missing consistent season branding visual element
2. Highlights Section Issues ⚠️
- Link Prioritization Problem: Only 1 out of 6 highlights links to preferred Microsoft domains
- Current links include external sites (Hugging Face, Meta) that should be secondary
- Recommendation: Prioritize
https://techcommunity.microsoft.com/blogs/andhttps://devblogs.microsoft.com/foundry/links - Contains 6 highlights instead of exactly 5 as specified
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.
- 21d ago First seen · 159 lines · 0 tokens per session scan A d29b1342a790
blog-review-example is a command published in the GitHub repository microsoft/model-mondays (301 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,505 tokens. 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 2026-09-25.
Other commands, from other repositories
vibe-workflow
The vibe-coding workflow turns an app idea into a working MVP in 5 stages. Your job: figure out where the user is and route them to the right stage.
vibe-agents
Step 4 of the vibe-coding workflow: generate AGENTS.md + tool configs so the AI builder stays on track.
vibe-build
Step 5 of the vibe-coding workflow: build the MVP one verified feature at a time.
vibe-prd
Step 2 of the vibe-coding workflow: define WHAT to build, WHO it's for, and WHY it matters.
vibe-research
Step 1 of the vibe-coding workflow: validate the app idea with deep research before anything gets built.
vibe-techdesign
Step 3 of the vibe-coding workflow: plan HOW to build it — stack, architecture, costs, deployment.