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 skills add microsoft/Generative-AI-for-beginners-dotnet --skill economy-modegit 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/economy-mode)<a href="https://agentmods.dev/skills/microsoft/generative-ai-for-beginners-dotnet/economy-mode"><img src="https://agentmods.dev/badge/skills/microsoft/generative-ai-for-beginners-dotnet/economy-mode/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/microsoft/generative-ai-for-beginners-dotnet/economy-mode"><img src="https://agentmods.dev/badge/skills/microsoft/generative-ai-for-beginners-dotnet/economy-mode.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 | $0.00022 | $0.01302 |
| Opus 5 | $0.00011 | $0.00651 |
| Sonnet 5 | $0.00004 | $0.00260 |
| Haiku 4.5 | $0.00002 | $0.00130 |
Grade A, and why
economy-mode 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 11d 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.
Copies of this mod
7 near-identical copies found in the catalogue:
- economy-mode — 100% identical, 0 lines differ
- economy-mode — 100% identical, 0 lines differ
- economy-mode — 100% identical, 0 lines differ
- economy-mode — 100% identical, 228 lines differ
- economy-mode — 100% identical, 0 lines differ
- economy-mode — 100% identical, 0 lines differ
- economy-mode — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SCOPE
✅ THIS SKILL PRODUCES:
- A modified Layer 3 model selection table applied when economy mode is active
economyMode: truewritten to.squad/config.jsonwhen activated persistently- Spawn acknowledgments with
💰indicator when economy mode is active
❌ THIS SKILL DOES NOT PRODUCE:
- Code, tests, or documentation
- Cost reports or billing artifacts
- Changes to Layer 0, Layer 1, or Layer 2 resolution (user intent always wins)
Context
Economy mode shifts Layer 3 (Task-Aware Auto-Selection) to lower-cost alternatives. It does NOT override persistent config (defaultModel, agentModelOverrides) or per-agent charter preferences — those represent explicit user intent and always take priority.
Use this skill when the user wants to reduce costs across an entire session or permanently, without manually specifying models for each agent.
Activation Methods
| Method | How |
|---|---|
| Session phrase | "use economy mode", "save costs", "go cheap", "reduce costs" |
| Persistent config | "economyMode": true in .squad/config.json |
| CLI flag | squad --economy |
Deactivation: "turn off economy mode", "disable economy mode", or remove economyMode from config.json.
Economy Model Selection Table
When economy mode is active, Layer 3 auto-selection uses this table instead of the normal defaults:
| Task Output | Normal Mode | Economy Mode |
|---|---|---|
| Writing code (implementation, refactoring, bug fixes) | claude-sonnet-4.5 |
gpt-4.1 or gpt-5-mini |
| Writing prompts or agent designs | claude-sonnet-4.5 |
gpt-4.1 or gpt-5-mini |
| Docs, planning, triage, changelogs, mechanical ops | claude-haiku-4.5 |
gpt-4.1 or gpt-5-mini |
| Architecture, code review, security audits | claude-opus-4.5 |
claude-sonnet-4.5 |
| Scribe / logger / mechanical file ops | claude-haiku-4.5 |
gpt-4.1 |
Prefer gpt-4.1 over gpt-5-mini when the task involves structured output or agentic tool use. Prefer gpt-5-mini for pure text generation tasks where latency matters.
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.
- 11d ago First seen · 115 lines · 22 tokens per session scan A bf9b5fc4a3af
economy-mode is a skill published in the GitHub repository microsoft/Generative-AI-for-beginners-dotnet (3,058 stars, last pushed 10d ago), licensed MIT. It adds 22 tokens to every session and 1,302 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
tidy-skill
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terminal-management
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azure-ml-model-evaluation
Evaluate generative AI applications and models locally or in the cloud using Azure AI Evaluation SDK. Measure quality, safety, and performance with built-in and custom evaluators.
azure-ml-dataset-creator
Generate synthetic and simulated datasets for evaluation and fine-tuning using Azure AI Foundry simulators. Create non-adversarial task data, adversarial safety data, and conversation datasets without manual data collection.
azure-ml-llm-trainer
Train or fine-tune LLMs on Azure ML managed compute with TRL trainers. Uses direct trainer loops (SFT, DPO, RL) without relying on serverless APIs or Hugging Face infrastructure.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.