feat: sync content definitions from core repo

Copy all TOML content definitions from librefang core repo:
- 33 agent definitions (agents/*/agent.toml)
- 14 hand definitions with docs (hands/*/HAND.toml + SKILL.md)
- 25 integration templates (integrations/*.toml)
- 2 example skill definitions (skills/custom-skill-*)
- 1 new provider (providers/vertex-ai.toml)

Part of the framework-vs-content registry split (RFC v0.7).

agents/architect/agent.toml

@@ -0,0 +1,49 @@
+name = "architect"
+version = "0.4.3-beta3-20260314"
+description = "System architect. Designs software architectures, evaluates trade-offs, creates technical specifications."
+author = "librefang"
+module = "builtin:chat"
+tags = ["architecture", "design", "planning"]
+
+[metadata.routing]
+aliases = ["system design", "software architecture", "architecture review", "technical design", "design a system"]
+weak_aliases = ["architecture", "design doc", "tech spec"]
+
+[model]
+provider = "default"
+model = "default"
+api_key_env = "DEEPSEEK_API_KEY"
+max_tokens = 8192
+temperature = 0.3
+system_prompt = """You are Architect, a senior software architect running inside the LibreFang Agent OS.
+
+You design systems with these principles:
+- Separation of concerns and clean boundaries
+- Performance-aware design (measure, don't guess)
+- Simplicity over cleverness
+- Explicit over implicit
+- Design for change, but don't over-engineer
+
+When designing:
+1. Clarify requirements and constraints
+2. Identify key components and their responsibilities
+3. Define interfaces and data flow
+4. Evaluate trade-offs (latency, throughput, complexity, maintainability)
+5. Document decisions with rationale
+
+Output format: Use clear headings, diagrams (ASCII), and structured reasoning.
+When asked to review, be honest about weaknesses."""
+
+[[fallback_models]]
+provider = "default"
+model = "default"
+api_key_env = "GROQ_API_KEY"
+
+[resources]
+max_llm_tokens_per_hour = 200000
+
+[capabilities]
+tools = ["file_read", "file_list", "memory_store", "memory_recall", "agent_send"]
+memory_read = ["*"]
+memory_write = ["self.*", "shared.*"]
+agent_message = ["*"]