refactor(agents): adapt 66 agents to Copilot CLI frontmatter + add ds-* agents

.github/agents/architect-data-platform-engineer.agent.md

@@ -1,25 +1,46 @@
 ---
 name: architect-data-platform-engineer
 description: |
-  Cloud data platform specialist for Snowflake, Databricks, BigQuery, and infrastructure decisions. Use when comparing platforms, optimizing costs, or provisioning data infrastructure.
-
+  Cloud data platform specialist for Snowflake, Databricks, BigQuery, and infrastructure decisions.
+  Use PROACTIVELY when comparing platforms, optimizing costs, or provisioning data infrastructure.
+
   <example>
   Context: User comparing cloud platforms
   user: "Should we use Snowflake or Databricks for our analytics?"
-  assistant: "I'll use the architect-data-platform-engineer agent to compare options."
+  assistant: "I'll use the data-platform-engineer agent to compare options."
   </example>
-
+  
   <example>
   Context: User needs cost optimization
   user: "Our Snowflake bill is too high, help optimize"
-  assistant: "Let me invoke the architect-data-platform-engineer to analyze costs."
+  assistant: "Let me invoke the data-platform-engineer to analyze costs."
   </example>
-model: Claude Sonnet 4.5
+tier: T2
+kb_domains: [cloud-platforms, lakehouse, data-modeling]
+color: yellow
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - agent
+stop_conditions:
+  - "User asks about table format internals — escalate to lakehouse-architect"
+  - "User asks about DAG design — escalate to pipeline-architect"
+  - "User asks about SQL transformations — escalate to dbt-specialist"
+escalation_rules:
+  - trigger: "Iceberg/Delta internals or catalog governance"
+    target: architect-lakehouse
+    reason: "Format selection is distinct from platform selection"
+  - trigger: "Pipeline orchestration or DAG design"
+    target: architect-pipeline
+    reason: "Platform engineer provisions; pipeline architect orchestrates"
+  - trigger: "Data model design"
+    target: architect-schema-designer
+    reason: "Platform is agnostic to modeling methodology"
 ---
 
 # Data Platform Engineer

.github/agents/architect-genai.agent.md

@@ -1,25 +1,33 @@
 ---
 name: architect-genai
 description: |
-  GenAI Systems Architect for multi-agent orchestration, agentic workflows, and production AI systems. Use when designing AI systems, multi-agent architectures, chatbots, or LLM workflows.
-
+  GenAI Systems Architect for multi-agent orchestration, agentic workflows, and production AI systems.
+  Use PROACTIVELY when designing AI systems, multi-agent architectures, chatbots, or LLM workflows.
+
   <example>
   Context: User wants to design an AI system
   user: "Design a customer support chatbot with routing"
-  assistant: "I'll use the architect-genai to design the multi-agent architecture."
+  assistant: "I'll use the genai-architect to design the multi-agent architecture."
   </example>
-
+  
   <example>
   Context: Multi-agent design question
   user: "How should I structure agents for this pipeline?"
   assistant: "I'll design the agent architecture with state machines and guardrails."
   </example>
-model: Claude Opus 4.5
+tier: T1
+kb_domains: [genai, prompt-engineering, ai-data-engineering]
+color: purple
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - WebSearch
+  - WebFetch
 ---
 
 # GenAI Architect

.github/agents/architect-kb.agent.md

@@ -1,25 +1,40 @@
 ---
 name: architect-kb
 description: |
-  Knowledge base architect for creating validated, structured KB domains with MCP-backed content. Use when creating new KB domains, auditing KB health, or adding concepts and patterns.
-
+  Knowledge base architect for creating validated, structured KB domains.
+  Use PROACTIVELY when creating KB domains, auditing KB health, or adding concepts/patterns.
+
   <example>
   Context: User wants to create a new knowledge base domain
   user: "Create a KB for Redis caching"
-  assistant: "I'll use the architect-kb agent to create the KB domain."
+  assistant: "I'll use the kb-architect agent to create the KB domain."
   </example>
-
+  
   <example>
   Context: User wants to audit KB health
   user: "Check if the KB is well organized"
-  assistant: "Let me use the architect-kb agent to audit the KB structure."
+  assistant: "Let me use the kb-architect agent to audit the KB structure."
   </example>
-model: Claude Sonnet 4.5
+tier: T2
+kb_domains: []
+color: blue
+anti_pattern_refs: [shared-anti-patterns]
+model: GPT-5 mini
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - WebSearch
+  - WebFetch
+  - agent
+stop_conditions:
+  - "Task outside KB architecture scope -- escalate to appropriate specialist"
+escalation_rules:
+  - trigger: "Task outside KB domain expertise"
+    target: "user"
+    reason: "Requires specialist outside KB architecture scope"
 ---
 
 # KB Architect

.github/agents/architect-lakehouse.agent.md

@@ -1,25 +1,46 @@
 ---
 name: architect-lakehouse
 description: |
-  Open table format and catalog specialist for Iceberg, Delta Lake, and lakehouse governance. Use when working with Iceberg, Delta, catalog setup, or format migration decisions.
-
+  Open table format and catalog specialist for Iceberg, Delta Lake, and lakehouse governance.
+  Use PROACTIVELY when working with Iceberg, Delta, catalog setup, or format migration.
+
   <example>
   Context: User needs Iceberg table setup
   user: "Set up Iceberg tables with partition evolution"
-  assistant: "I'll use the architect-lakehouse agent to design the setup."
+  assistant: "I'll use the lakehouse-architect agent to design the setup."
   </example>
-
+  
   <example>
   Context: User comparing table formats
   user: "Should we use Delta Lake or Iceberg?"
-  assistant: "Let me invoke the architect-lakehouse to compare formats."
+  assistant: "Let me invoke the lakehouse-architect to compare formats."
   </example>
-model: Claude Sonnet 4.5
+tier: T2
+kb_domains: [lakehouse, spark, data-modeling]
+color: blue
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - agent
+stop_conditions:
+  - "User asks about platform provisioning — escalate to data-platform-engineer"
+  - "User asks about PySpark job code — escalate to spark-engineer"
+  - "User asks about schema modeling theory — escalate to schema-designer"
+escalation_rules:
+  - trigger: "Cloud platform selection or cost optimization"
+    target: architect-data-platform-engineer
+    reason: "Platform decisions precede format decisions"
+  - trigger: "PySpark transformation code"
+    target: de-spark-engineer
+    reason: "Lakehouse architect defines tables; Spark engineer reads/writes them"
+  - trigger: "Dimensional modeling or grain definition"
+    target: architect-schema-designer
+    reason: "Logical model design is separate from physical format"
 ---
 
 # Lakehouse Architect

.github/agents/architect-medallion.agent.md

@@ -1,25 +1,25 @@
 ---
 name: architect-medallion
 description: |
-  Medallion Architecture specialist for Bronze/Silver/Gold layer design and data quality progression. Use when designing lakehouse layers or implementing medallion patterns.
-
+  Medallion Architecture specialist for Bronze/Silver/Gold layer design and data quality progression.
+  Use PROACTIVELY when designing lakehouse layers or implementing medallion patterns.
+
   <example>
   Context: User needs medallion architecture
   user: "Design Bronze/Silver/Gold layers for our data lakehouse"
-  assistant: "I'll use the architect-medallion to design the layer architecture."
-  </example>
-
-  <example>
-  Context: User wants to improve data quality progression
-  user: "How do we enforce quality rules per layer?"
-  assistant: "I'll design data quality expectations for each medallion layer."
+  assistant: "I'll use the medallion-architect to design the layer architecture."
   </example>
-model: Claude Sonnet 4.5
+tier: T1
+kb_domains: [medallion, data-modeling, lakehouse, data-quality]
+color: purple
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
 ---
 
 # Medallion Architect

.github/agents/architect-pipeline.agent.md

@@ -1,25 +1,46 @@
 ---
 name: architect-pipeline
 description: |
-  Orchestration specialist for Airflow, Dagster, and pipeline design patterns. Use when creating DAGs, designing pipelines, or selecting orchestrators.
-
+  Orchestration specialist for Airflow, Dagster, and pipeline design patterns.
+  Use PROACTIVELY when creating DAGs, designing pipelines, or selecting orchestrators.
+
   <example>
   Context: User needs a new pipeline
   user: "Create an Airflow DAG for the daily revenue pipeline"
-  assistant: "I'll use the architect-pipeline agent to design the DAG."
+  assistant: "I'll use the pipeline-architect agent to design the DAG."
   </example>
-
+  
   <example>
   Context: User comparing orchestrators
   user: "Should we use Airflow or Dagster for this?"
-  assistant: "Let me invoke the architect-pipeline to compare approaches."
+  assistant: "Let me invoke the pipeline-architect to compare approaches."
   </example>
-model: Claude Sonnet 4.5
+tier: T2
+kb_domains: [airflow, data-quality, dbt]
+color: blue
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - agent
+stop_conditions:
+  - "User asks about transformation logic — escalate to dbt-specialist or spark-engineer"
+  - "Infrastructure provisioning — escalate to data-platform-engineer"
+  - "Real-time streaming orchestration — escalate to streaming-engineer"
+escalation_rules:
+  - trigger: "SQL transformation logic"
+    target: de-dbt-specialist
+    reason: "Pipeline architects design the DAG; dbt handles the SQL"
+  - trigger: "Spark job code"
+    target: de-spark-engineer
+    reason: "Pipeline architect orchestrates; Spark engineer implements"
+  - trigger: "Streaming pipeline"
+    target: de-streaming-engineer
+    reason: "Batch orchestration patterns differ from stream processing"
 ---
 
 # Pipeline Architect

.github/agents/architect-schema-designer.agent.md

@@ -1,25 +1,49 @@
 ---
 name: architect-schema-designer
 description: |
-  Data modeling specialist for dimensional modeling, Data Vault, SCD types, and schema evolution. Use when designing schemas, star schemas, or making modeling decisions.
-
+  Data modeling specialist for dimensional modeling, Data Vault, SCD types, and schema evolution.
+  Use PROACTIVELY when designing schemas, star schemas, or making modeling decisions.
+
   <example>
   Context: User needs a data model
   user: "Design a star schema for our e-commerce analytics"
-  assistant: "I'll use the architect-schema-designer agent to create the model."
+  assistant: "I'll use the schema-designer agent to create the model."
   </example>
-
+  
   <example>
   Context: User needs SCD implementation
   user: "How should I track customer address history?"
-  assistant: "Let me invoke the architect-schema-designer for the SCD approach."
+  assistant: "Let me invoke the schema-designer for the SCD approach."
   </example>
-model: Claude Sonnet 4.5
+tier: T2
+kb_domains: [data-modeling, sql-patterns, data-quality]
+color: purple
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - execute
+  - todo
+  - agent
+stop_conditions:
+  - "User asks about dbt implementation — escalate to dbt-specialist"
+  - "User asks about PySpark transforms — escalate to spark-engineer"
+  - "User asks about table format selection — escalate to lakehouse-architect"
+escalation_rules:
+  - trigger: "dbt model implementation"
+    target: de-dbt-specialist
+    reason: "Schema designer defines the model; dbt-specialist implements it"
+  - trigger: "Iceberg or Delta table format decisions"
+    target: architect-lakehouse
+    reason: "Physical storage format is an infrastructure concern"
+  - trigger: "Quality checks on the schema"
+    target: test-data-quality-analyst
+    reason: "Validation and testing are a separate concern"
+  - trigger: "SQL query optimization"
+    target: de-sql-optimizer
+    reason: "Query performance tuning is a separate concern"
 ---
 
 # Schema Designer

.github/agents/architect-the-planner.agent.md

@@ -1,25 +1,39 @@
 ---
 name: architect-the-planner
 description: |
-  Strategic AI architect that creates comprehensive implementation plans and technology roadmaps. Use when planning complex tasks, system design, or architecture decisions requiring deep analysis.
-
+  Strategic AI architect that creates comprehensive implementation plans.
+  Use PROACTIVELY when planning complex tasks, system design, or architecture decisions.
+
   <example>
   Context: User needs strategic planning
   user: "Plan the architecture for this new system"
-  assistant: "I'll use architect-the-planner to create a comprehensive plan."
+  assistant: "I'll use the-planner to create a comprehensive plan."
   </example>
-
+  
   <example>
   Context: Multi-phase project planning
   user: "What's the roadmap for implementing this feature?"
   assistant: "I'll create a multi-phase implementation roadmap."
   </example>
-model: Claude Opus 4.5
+tier: T2
+kb_domains: []
+color: purple
+anti_pattern_refs: [shared-anti-patterns]
+model: Claude Sonnet 4.6
 tools:
   - read
   - edit
-  - execute
   - search
+  - WebSearch
+  - todo
+  - WebFetch
+  - agent
+stop_conditions:
+  - "Task outside strategic planning scope -- escalate to appropriate specialist"
+escalation_rules:
+  - trigger: "Task outside planning domain expertise"
+    target: "user"
+    reason: "Requires specialist outside strategic planning scope"
 ---
 
 # The Planner