Borrowing it
Nothing to install: this file belongs to dotnet-presentations/ai-workshop. 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/dotnet-presentations/ai-workshop/main/.github/instructions/genailab.instructions.mdgit clone --depth 1 https://github.com/dotnet-presentations/ai-workshopWrote 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/instructions/dotnet-presentations/ai-workshop/genailab)<a href="https://agentmods.dev/instructions/dotnet-presentations/ai-workshop/genailab"><img src="https://agentmods.dev/badge/instructions/dotnet-presentations/ai-workshop/genailab/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/instructions/dotnet-presentations/ai-workshop/genailab"><img src="https://agentmods.dev/badge/instructions/dotnet-presentations/ai-workshop/genailab.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 | $0.00348 | $0.00348 |
| Opus 5.5 | $0.00139 | $0.00139 |
| Sonnet 5.5 | $0.00070 | $0.00070 |
| Haiku 4.5 | $0.00035 | $0.00035 |
Grade A, and why
ai-workshop genailab.instructions.md 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.
What it actually says
GenAiLab progression
- Treat Parts 4, 10, and 11 as one app progression. Part 4 scaffolds GenAiLab, Part 10 changes its production service choices, and the Part 11 snapshot is the deployment-ready result.
- Read
docs/instructor/DEPENDENCY_POLICY.mdbefore changing package versions in this progression. Preserve its security overrides and coordinated Aspire set. - Preserve the exact Part 4 scaffold command unless intentionally updating the entire progression. Its provider, vector-store, Aspire, name, and output options determine what later instructions can assume.
- The AppHost deliberately uses the existing Azure OpenAI connection instead of provisioning a new account. Preserve that behavior and the corresponding attendee step across Parts 4 and 11.
- Keep Azure AI Search as the recommended Part 10/11 production path and Qdrant as the documented fallback unless the workshop's provider strategy changes.
- When template output, package requirements, or infrastructure behavior changes,
verify the current template and update the relevant READMEs, Part 11 snapshot,
and
docs/instructor/AICHATWEB_TEMPLATE_NOTES.mdtogether. - Do not commit
azure.yamlor.azure/; deployment initialization generates them at runtime.
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 · 26 lines · 348 tokens per session scan A 257c6950ba23
ai-workshop genailab.instructions.md is an instructions file published in the GitHub repository dotnet-presentations/ai-workshop (62 stars, last pushed 4d ago), licensed MIT. It adds 348 tokens to every session, about $0.0014 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 2026-09-08.
ai-workshop genailab.instructions.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-workshop genailab.instructions.mddotnet-presentations/ai-workshop | Instructions file | 62 | 4d ago | MIT | A | 348 | GitHub Copilot |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |