fix(ms-ai-architect): Foundry URL-navnerom-migrering (ai-foundry → foundry/foundry-classic, 141 filer)

Task #5 del 1/3 (URL-migrering). Verifiseringen motbeviste STATE.md-premisset om ren prefix-swap: rebrand er per-URL, ikke mekanisk. En blind sed ai-foundry→foundry ville lagd 56 nye 404-er (classic-stiene finnes ikke under nytt foundry/-prefiks — bekreftet empirisk).

Metode: resolverte alle 237 unike KB-URLer mot live redirects (curl -L), bygde full-URL→full-URL-mapping fra faktisk url_effective. Bevarer locale-form, query (?view=) og #fragment per lenke.

- 231 navnerom-erstatninger over 141 filer (408 forekomster):
  - 161 → azure/foundry/ (98 ren prefix-swap + 10 sti-reorg + reorg-tilfeller)
  - 69 → azure/foundry-classic/ (eldre hub-spor: assistants, hub-DR, on-your-data; faktisk redirect-mål per operatorvalg)
  - 1 → azure/foundry-local/

- 2 døde lenker (404) fikset til verifiserte mål:
  - agent-service → azure/foundry/agents/overview
  - concepts/evaluation-evaluators/ → azure/foundry/how-to/evaluate-generative-ai-app

- 5 path-/display-referanser (uten https://, i backticks/lenketekst) rettet manuelt.

- 6 slug-baserte ai-foundry-treff urørt (scope-grense): managed-grafana-dashboard, security-baseline, power-platform prompt-builder, architecture baseline-chat (sistnevnte slug-rebrand i annet navnerom — mulig fremtidig funn).

- Parkert til task #5 del 2/3: Norway East GPT-5-datasuverenitet-fiks + modellkatalog-utvidelse (5.3/5.4/5.5, gpt-oss, sora-2).

Verifisert: 0 gjenværende azure/ai-foundry/-navnerom i skills/. validate-plugin.sh 219 PASS. test-kb-integrity.sh 117/117 passed.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Claude-Session: https://claude.ai/code/session_01REiKFhP4w6xGXXqWKpPCJJ

skills/ms-ai-engineering/references/data-engineering/data-anonymization-privacy.md

@@ -549,11 +549,11 @@ def privacy_check_before_deployment(model_artifacts_path: str) -> dict:
 ## Referanser
 
 - [What is Azure Language PII detection?](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/overview) -- PII-deteksjon og maskering
-- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er
+- [PII filter in Azure AI Foundry](https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/content-filter-personal-information) -- PII-filtrering for LLM-er
 - [Responsible AI - Privacy and security](https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai) -- SmartNoise og Counterfit
 - [Data privacy for cloud-scale analytics](https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/secure-data-privacy) -- Dataklassifisering og konfidensialitetsskjema
 - [PII entity categories](https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories) -- Alle stottede PII-kategorier
-- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger
+- [Transparency note for PII](https://learn.microsoft.com/en-us/azure/foundry/responsible-ai/language-service/transparency-note-personally-identifiable-information) -- Bruksomrader og begrensninger
 - [Data governance with Microsoft Purview](https://learn.microsoft.com/en-us/purview/data-governance-master-data-management) -- Purview for dataklassifisering
 
 ---

skills/ms-ai-engineering/references/data-engineering/data-quality-ai-frameworks.md

@@ -550,7 +550,7 @@ def trigger_purview_profiling(data_asset_id, connection_id):
 ### Code samples (Microsoft Learn)
 
 - **Azure ML fine-tuning job with validation data**
-  https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/fine-tune-serverless
+  https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/fine-tune-serverless
   Python SDK sample for creating validation dataset asset.
 
 - **AutoML training/validation MLTable inputs**

skills/ms-ai-engineering/references/data-engineering/synthetic-data-generation.md

@@ -408,11 +408,11 @@ for metric, result in validation.items():
 
 ## Referanser
 
-- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator
-- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI
+- [Generate synthetic and simulated data for evaluation](https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/develop/simulator-interaction-data) -- Azure AI Evaluation Simulator
+- [Generate synthetic data for fine-tuning in Microsoft Foundry](https://learn.microsoft.com/en-us/azure/foundry/fine-tuning/data-generation) -- Foundry syntetisk data UI
 - [Design training data for AI workloads on Azure](https://learn.microsoft.com/en-us/azure/well-architected/ai/training-data-design) -- Well-Architected Framework for treningsdata
 - [Azure OpenAI for big data](https://learn.microsoft.com/en-us/fabric/data-science/open-ai) -- SynapseML + OpenAI på Fabric
-- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) -- RAG for datagenerering
+- [Azure OpenAI On Your Data](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) -- RAG for datagenerering
 
 ---