MicroHack / 11_Healthcare_Regulatory_Intelligence
Copilot instructions220 starsChanged 7 days agoMITView on GitHub
This workspace is a microhack lab for the EMEA MicroHack platform (microsoft/MicroHack). The platform renders a front-end UI, but all resource provisioning comes from labautomation/deploy-lab.ps1. Without a working deployment script, no resources appear in the Azure portal; the platform is just a shiny front end. The platform skips the script if the parameter block does not exactly match: Write a hashtable to the output stream. The platform captures it and shows it on the user's dashboard: This workspace is 11_Healthcare_Regulatory_Intelligence.…
Where files are headingNew Copilot instructions files have more rules about branches and pull requests, and fewer about code style.
Of the Copilot instructions files we read, the 2,349 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository11 other files it gives its agents.
- 03-Azure/01-04-AI/01_Agentic_SDLC/.github/copilot-instructions.mdCopilot instructions
- 03-Azure/01-04-AI/02_Inventory_Planning_Fabric/.github/copilot-instructions.mdCopilot instructions
- 03-Azure/01-04-AI/03_Inventory_Planning_Agentic/.github/copilot-instructions.mdCopilot instructions
- 03-Azure/01-04-AI/04_Agentic_Contract_Lifecycle_Management/.github/copilot-instructions.mdCopilot instructions
- 03-Azure/01-04-AI/08_Predictive_Maintenance/.github/copilot-instructions.mdCopilot instructions
- dotnet-upgradeSkill
- java-upgradeSkill
- {{skill-name-kebab-case}}Skill
- skill-creatorSkill
- frontend-designSkill
- reconciliationSkill
The file
We split this copilot-instructions.md into the rules it gives an agent
5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 67
Write a hashtable to the output stream.
- Distinctive: line 76
Keep changes confined to this lab and its explicit catalogue link.
- Very specific: line 81
Do not frame the workshop as an adaptation of another MicroHack, and do not add attribution sections.
- Very specific: line 96
Keep infrastructure templates in infra/, not labautomation/.
- Distinctive: line 101
Do not hard-code corporate network or specific DNS assumptions.
≈ “Common” is an estimate: at least 1 in 5 of the 3,779 Copilot instructions files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
MicroHack Lab: EMEA Platform Conventions
This workspace is a microhack lab for the EMEA MicroHack platform (microsoft/MicroHack).
The platform renders a front-end UI, but all resource provisioning comes from labautomation/deploy-lab.ps1.
Without a working deployment script, no resources appear in the Azure portal; the platform is just a shiny front end.
Mandatory Structure
labautomation/ ← exactly this name, no dashes
deploy-lab.ps1 ← platform entry point (optional but recommended)
lab-defaults.json ← platform configuration (required if folder exists)
README.md ← usage notes
challenges/ ← challenge instructions (Markdown)
walkthrough/ ← solutions
README.md ← hack intro, objectives, prerequisitesdeploy-lab.ps1: Parameter Contract
The platform skips the script if the parameter block does not exactly match:
param(
[Parameter(Mandatory=$true)]
[ValidateSet('subscription','resourcegroup','resourcegroup-with-subscriptionowner')]
[string]$DeploymentType,
[Parameter(Mandatory=$true)]
[string]$SubscriptionId,
[string]$ResourceGroupName = "",
[string[]]$PreferredLocation = @(),
[string[]]$AllowedEntraUserIds = @()
)Platform Guarantees (before your script runs)
- Az context is already set to
$SubscriptionId, so do NOT callConnect-AzAccount - For
resourcegroup/resourcegroup-with-subscriptionowner: the RG exists and your script hasOwner, so do NOT callNew-AzResourceGroup - For
subscription: your script hasOwneron the subscription; you must create the RG yourself usingGet-MhhStableHashfor deterministic naming Az.AccountsandAz.Resourcesmodules are already imported
lab-defaults.json: Required Shape
{
"$schema": "https://raw.githubusercontent.com/microsoft/MicroHack/refs/heads/main/lab-defaults-schema.json",
"groups": [],
"deploymentType": "resourcegroup",
"labsPerSubscription": 4,
"preferredLocation": "uksouth",
"estimatedDailyCostsUsd": 15.0
}deploymentType:"resourcegroup"|"resourcegroup-with-subscriptionowner"|"subscription"groups:[](Azure only),["GHCPUsers"](GitHub Copilot seat),["M365-E5-Users"](M365 E5)preferredLocation: comma-separated regions, priority orderestimatedDailyCostsUsd: per-user per-day cost for the lifecycle wizard
Returning Credentials to Users
Write a hashtable to the output stream. The platform captures it and shows it on the user's dashboard:
@{ HackboxCredential = @{ name = "ResourceGroupName"; value = $ResourceGroupName; note = "Dedicated training resources" } }Regulatory Intelligence Scope
This workspace is 11_Healthcare_Regulatory_Intelligence.
Keep changes confined to this lab and its explicit catalogue link.
The storyline: Caldova Health Services Ltd, a fictional UK life-sciences company, sells one medicine, Caldivex (tablets CDX-TAB, injection pen CDX-PEN). Keep the cast that small: everyone else is a role (Labelling Lead, Quality Head, ...). Do not frame the workshop as an adaptation of another MicroHack, and do not add attribution sections.
The hack implements the healthcare and life sciences regulatory-intelligence case
overview: Regulatory Web & Change Monitor, Document & Citation Agent, Obligation &
Impact Extractor, Regulatory Q&A Assistant and Executive Briefing with human
sign-off. Participants build prompt agents in the Foundry portal over a Foundry IQ
knowledge base on the regulatory-knowledge Blob container.
Crawling, de-duplication, versioning and recording sign-off are deterministic code
in regintel/ (Python standard library only, Python 3.9+ for Cloud Shell). Agents
read, link, explain and summarise; they propose, never approve. All publications,
products and dates are fictional. Keep tests/ passing and update expected answers
in walkthrough/ when the data in data/ changes.
Keep infrastructure templates in infra/, not labautomation/. Do not add a
cross-region fallback without explicit approval.
Platform Compatibility
The platform supports on-site, online, and hybrid delivery. Do not hard-code corporate network or specific DNS assumptions.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

