chore(privacy): scrub real-org references from plugin internals (phase 2)

Same bulk replacement applied to plugin-internal KB, examples, fixtures,
tests, and docs. Real organization names, persona names, internal system
identifiers, and domain-specific terms replaced with fictional generic
public-sector entity (DDT) and generic terminology.

Scope:
- okr/ — examples, governance, framework, integrations, sources
- ms-ai-architect/ — KB references (engineering, governance, security,
  infrastructure, advisor), tests/fixtures, agents, docs
- linkedin-thought-leadership/ — voice samples, network-builder,
  examples (genericized identifying headlines to "[your organization]")
- llm-security/ — research notes, scan report

Manual genericization beyond bulk replace:
- okr SKILL.md "Primary user / Domain" — generic Norwegian public sector
- linkedin-voice SKILL.md headline placeholder
- network-builder.md headline placeholder
- high-engagement-posts.md voice sample employer line + hashtag

Phase 3 (factual-attribution review) remains: a few KB files attribute
publicly known transport-sector docs/datasets (e.g. håndbok V440, NVDB)
to the fictional DDT after bulk replace. Needs manual semantic review
to either remove or restore correct citation without re-introducing
affiliation references.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

skills/ms-ai-engineering/references/data-engineering/data-cataloging-discovery.md

@@ -170,7 +170,7 @@ Unified Catalog tilbyr flere oppdagelsesmekanismer for å finne data:
 ```
 Eksempler på naturlig språk-søk (preview):
 
-Søk: "Jeg trenger tre år med trafikkdata fra Statens vegvesen
+Søk: "Jeg trenger tre år med trafikkdata fra Direktoratet for digital tjenesteutvikling
        for å analysere rushtrafikk-mønstre"
 Resultat: Data products med trafikktelledata, reisehastighetsmålinger
 
@@ -381,7 +381,7 @@ ai_terms = [
                        "skal predikere på.",
         "abbreviation": "TD",
         "glossary_guid": ai_glossary_guid,
-        "owner": "ml-team@vegvesen.no",
+        "owner": "ml-team@ddt.no",
         "regulation": "GDPR Art. 6 - Lovlig behandlingsgrunnlag"
     },
     {
@@ -389,7 +389,7 @@ ai_terms = [
         "definition": "Sentralisert repository for beregning, lagring og "
                        "servering av ML-features med punkt-i-tid korrekthet.",
         "glossary_guid": ai_glossary_guid,
-        "owner": "data-engineering@vegvesen.no"
+        "owner": "data-engineering@ddt.no"
     },
     {
         "name": "Dataminimering",
@@ -518,9 +518,9 @@ def assign_data_owner(purview_endpoint, token, asset_guid, owner_info):
 
 # Eksempel: Tilordne eierskap for ML-datasett
 assign_data_owner(endpoint, token, gold_features_guid, {
-    "email": "ml-team@vegvesen.no",
+    "email": "ml-team@ddt.no",
     "aad_object_id": "abc-123-def",
-    "expert_email": "data-scientist@vegvesen.no",
+    "expert_email": "data-scientist@ddt.no",
     "expert_aad_id": "ghi-456-jkl"
 })
 ```