Generative AI for Beginners .NET is a hands-on course that teaches .NET developers to build applications using generative AI models and related tools. Its lessons use practical samples covering scenarios such as chat, audio transcription, agents, and local AI. The catalogue entries are add-ons associated with the course repository.
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/generative-ai-for-beginners-dotnet/napnpx skills add microsoft/Generative-AI-for-beginners-dotnet --skill napgit clone --depth 1 https://github.com/microsoft/Generative-AI-for-beginners-dotnetWrote 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/generative-ai-for-beginners-dotnet/nap)<a href="https://agentmods.dev/skills/microsoft/generative-ai-for-beginners-dotnet/nap"><img src="https://agentmods.dev/badge/skills/microsoft/generative-ai-for-beginners-dotnet/nap.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 | $0.00015 | $0.00208 |
| Opus 5 | $0.00008 | $0.00104 |
| Sonnet 5 | $0.00003 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
nap 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.
This is a copy
100% identical to nap — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Skill: nap
Context hygiene — compress, prune, archive .squad/ state
What It Does
Reclaims context window budget by compressing agent histories, pruning old logs, archiving stale decisions, and cleaning orphaned inbox files.
When To Use
- Before heavy fan-out work (many agents will spawn)
- When history.md files exceed 15KB
- When .squad/ total size exceeds 1MB
- After long-running sessions or sprints
Invocation
- CLI:
squad nap/squad nap --deep/squad nap --dry-run - REPL:
/nap//nap --dry-run//nap --deep
Confidence
medium — Confirmed by team vote (4-1) and initial implementation
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 · 33 lines · 15 tokens per session scan A fb74fd3df58a
nap is a skill published in the GitHub repository microsoft/Generative-AI-for-beginners-dotnet (3,048 stars, last pushed 5d ago), licensed MIT. It adds 15 tokens to every session and 208 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to nap, differing in 0 lines, and is treated as a copy.
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