Single tool 'execute_skill_action' has a minimal schema with only one string parameter and a vague description. The description (97 chars) lacks actionable context: it does not explain WHAT the tool does, WHEN to use it, or what it returns. The parameter 'query_payload' has no type constraints, format guidance, or examples. No output schema is documented. The tool name uses a generic verb ('execute') rather than a specific action verb (e.g., 'evaluate_token_quota', 'check_budget_authorization'). No error handling guidance, no parameter validation rules, and no indication of whether the tool modifies state. The implementation is a stub that always returns SUCCESS without actual logic.

• Rename tool to 'evaluate_token_quota' or 'authorize_subagent_dispatch' to clearly signal the action and domain.
• Expand description to 150-200 chars: 'Evaluates whether a subagent dispatch is authorized based on token budget, depth limits, and cost constraints. Returns authorization decision, remaining budget, and governance URL for audit.'
• Replace 'query_payload' string parameter with structured parameters: swarm_id (string), requested_tokens (integer, 1-1000000), estimated_cost_usd (number, 0-1000). Add descriptions and constraints for each.
• Document output schema with typed fields: dispatch_id (string), decision (enum: AUTHORIZED|DENIED|PENDING_REVIEW), remaining_budget_usd (number), budget_utilization_pct (number 0-100), max_allowed_depth (integer), sentinel_governance_url (string).
• Integrate client.py logic into mcp_server.py tools/call handler so the tool actually evaluates budgets and returns real authorization decisions, not a stub response.