Sven laptop
635a130f0b
### Summary of Changes
1. Documentation Consolidation:
• Relocated the docs/ folder and all repository .md files (README.md, DEPLOYMENT.md, DOCKER_README.md,
DOMAINS_README.md, GETTING_STARTED.md, CI_CD_PORTAINER_GUIDE.md, ADMIN_DEPLOYMENT_SUMMARY.md,
SECURITY_PRIVATE_FILES.md, handoff.md, azure-project-plan.md, plus service-specific READMEs) into .
• Updated document links in README.md.
2. AI Agent Project Map:
• Created PROJECT_MAP.md in the project root containing complete architecture diagrams, service specs, ports, DB
schemas, environment variables, and developer workflows.
• Added PROJECT_MAP.md to .gitignore.
3. Monitoring UI & Infrastructure Integration:
• Added monitoring_ui service to docker-compose.yml (port 5175).
• Configured Gitea workflow docker-build.yml for monitoring_ui builds.
• Added CORS middleware headers in index.js.
• Added nginx.conf copy step in Dockerfile.
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### Recommended Commit Message
docs: consolidate project documentation into monitoring_ui and add agent project map
- Move all markdown documentation files and docs/ folder into monitoring_ui/docs/
- Update documentation hub index (monitoring_ui/docs/README.md) with relative paths
- Generate comprehensive AI agent reference map (PROJECT_MAP.md) in repository root
- Add PROJECT_MAP.md and monitoring_ui build output/env overrides to .gitignore
- Integrate monitoring_ui service into docker-compose.yml and Gitea CI workflow
- Configure CORS handling in employee_api for monitoring dashboard access
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### Alternative Short Commit Message
refactor(docs): move docs to monitoring_ui and create AI agent PROJECT_MAP.md
3.0 KiB
Important: This skill provides guidance and recommended instructions to assist the AI system. Outputs are not guaranteed to be complete, correct, secure, or applicable to every scenario. Results should be reviewed and validated by a human before being applied. The AI model may choose not to follow all instructions exactly, and additional verification may be required.
Intent Gathering
Scope Triage (Step 2 — before prereq)
⛔ Scope triage — BEFORE prereq. Check for azd template markers (
azure.yaml+ IaC ininfra/).Skip triage when:
- User explicitly asks for cost estimates, service recommendations, or code analysis
- Empty workspace (prereq’s zero-code-path handles it)
- Code exists but no infra files (no
.bicep,.tf,azure.yaml, orinfra/dir) — full pipeline is the only sensible path- Intentionally vulnerable app signals (🛑 detection) — proceed to prereq directly
If azd template detected
⛔ You MUST read
azd-template-routing.mdfor detection criteria, gate presentation, and routing protocol.If NO azd template BUT infra files present
Ask ONE
ask_userquestion:
- Yes — analyze and deploy end-to-end (Recommended)
- Just scaffold Bicep/Terraform
- Just deploy it (I have IaC ready)
- Other
Option 1 / vague → full pipeline (Step 3). Any other → hand off to the
azure-prepareagent.
After Prereq Returns (Step 4 — scan-informed intent gathering)
Prereq has written prereq-output.json and context.json.components[] — this is the authoritative source for all downstream phases (prepare and scaffold consume context.json, not prereq-output.json).
Present the detected component boundaries before asking questions. Include each deployable component's path,
framework, and intended Azure compute model. For a SPA plus Azure Functions project, state both mappings
explicitly: the frontend remains its own hosting service and the backend remains a separate Function App.
Do not infer an SWA-managed API merely because the frontend uses /api routes.
Confirm the Azure target ("☁️ Azure target: {subscriptionName} ({subscriptionId})"). If the user wants a different subscription, write to context.json.overrides[].
Present scan results first, then ask only what prereq didn't answer (≤2 if mostly covered, ≤4 if gaps):
| # | Topic | Ask if... |
|---|---|---|
| 1 | App purpose | Not obvious from detectedStack + components[] |
| 3 | Data/storage | Prereq didn't detect DB/compose |
| 4 | Auth approach | No MSAL/passport/auth library detected |
| 5 | Scale | Always — prereq doesn't know traffic expectations |
⛔ Do NOT ask about stack/language (always answered by prereq) or budget (only if user mentioned cost). User corrections → context.json.overrides[]. Stop when covered or user says "just go."
Update intent: Merge scan results into context.json.intent. Set refinedFromScan: true and populate scanDiscoveredFacts[].