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 fact-checkinggit 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/fact-checking)<a href="https://agentmods.dev/skills/microsoft/generative-ai-for-beginners-dotnet/fact-checking"><img src="https://agentmods.dev/badge/skills/microsoft/generative-ai-for-beginners-dotnet/fact-checking/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/fact-checking"><img src="https://agentmods.dev/badge/skills/microsoft/generative-ai-for-beginners-dotnet/fact-checking.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 | $0.00036 | $0.00469 |
| Opus 5.5 | $0.00014 | $0.00188 |
| Sonnet 5.5 | $0.00007 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
fact-checking 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.
This is a copy
100% identical to fact-checking — 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: Fact Checking
Context
Codifies the challenger agent review output format and methodology so any agent performing fact-checking or review produces consistent, structured output.
Pattern
Review Methodology
For every claim or deliverable under review:
- Ask: "What evidence supports this? What would disprove it?"
- Generate counter-hypotheses and test them against available data
- Verify URLs, package names, API endpoints, and external references actually exist
- Flag confidence levels: ✅ Verified, ⚠️ Unverified, ❌ Contradicted
Review Output Format
When reviewing another agent's work, use this template:
### Fact Check — {deliverable name}
**Claims verified:** {count}
**Issues found:** {count}
| # | Claim | Status | Evidence/Notes |
|---|-------|--------|---------------|
| 1 | {claim} | ✅/⚠️/❌ | {supporting or contradicting evidence} |
**Counter-hypotheses tested:**
- {alternative explanation + result}
**Verdict:** {PASS / PASS WITH NOTES / NEEDS REVISION}
Confidence Levels
- ✅ Verified — evidence confirms the claim
- ⚠️ Unverified — cannot confirm or deny; suggest verification method
- ❌ Contradicted — evidence disproves the claim
Ceremony Integration
Auto-trigger this skill before any architecture decision, or when an agent claim contains superlatives or percentage thresholds (e.g., "saves 75%", "always", "never"). The coordinator spawns the challenger agent with:
Challenger — fact-check {agent}'s claim: "{claim}"
Cite evidence for every verdict. Max 3 investigation cycles.
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 · 61 lines · 36 tokens per session scan A f03e598d6790
fact-checking is a skill published in the GitHub repository microsoft/Generative-AI-for-beginners-dotnet (3,145 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 469 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to fact-checking, differing in 0 lines, and is treated as a copy.
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