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-security/references/cost-optimization/rag-query-cost-reduction.md

@@ -433,7 +433,7 @@ User → Container App LB → [Azure OpenAI Region 1]
 
 **Verified:**
 1. [Plan and manage costs of an Azure AI Search service](https://learn.microsoft.com/en-us/azure/search/search-sku-manage-costs) - Comprehensive cost minimization strategies, tier pricing, indexing optimization.
-2. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/use-your-data) - Exact token consumption per model, RAG pipeline breakdown, parameter impacts.
+2. [Azure OpenAI On Your Data - Token usage estimation](https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/use-your-data) - Exact token consumption per model, RAG pipeline breakdown, parameter impacts.
 3. [RAG chunking phase - Understand chunking economics](https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/rag/rag-chunking-phase) - Cache-Aside pattern, cost factors for chunking strategies.
 4. [Agentic retrieval in Azure AI Search - Pricing example](https://learn.microsoft.com/en-us/azure/search/agentic-retrieval-overview) - Detailed cost calculation for agentic retrieval with subqueries.
 5. [Tips for better performance in Azure AI Search](https://learn.microsoft.com/en-us/azure/search/search-performance-tips) - Query design optimization, search tier switching, cost-performance balance.