This server has severe definition quality issues. Tool definitions are minimal and lack critical schema documentation. execute_skill_action has no visible input schema in mcp_server.py. inspect_agent_lock_graph has a schema visible in client.py but is not properly registered as an MCP tool, it's a Python class method, not an MCP tool definition. Neither tool has descriptions longer than 20 characters (both are under the 34-char p10 baseline). No parameter descriptions exist. No output schemas are documented. The server does not follow MCP tool registration patterns.

• Add explicit MCP tool registration in mcp_server.py using proper MCP protocol. Define both tools with full JSON Schema input and output schemas, not as Python class methods.
• Write descriptions 50 - 200 characters long, answering: What does it do? When should the LLM call it? What does it return? Example: 'Analyzes lock allocation and wait-request graphs to detect deadlock cycles and race conditions. Returns cycle nodes and preemption status. Call this after collecting lock state from agents.'
• Add descriptions to all parameters. For lock_allocations_graph, specify: 'Object mapping agent names (string keys) to arrays of resource names they hold. Example: {"agent_A": ["resource_1"], "agent_B": ["resource_2"]}'.
• Document output schema with typed fields. Example: {"lock_audit_id": "string", "deadlock_cycle_detected": "boolean", "culprit_cycle_nodes": "array of strings", "automatic_preemption_resolved": "boolean", "lock_dependency_graph_url": "string (URI)"}.
• Add error handling guidance. If no deadlock is detected, return a clear success response. If input graphs are malformed, return an actionable error: 'Invalid lock_allocations_graph: expected object with string keys and array values.'