Single tool with minimal definition quality. Tool name 'execute_skill_action' is generic and does not follow verb_noun pattern clearly (execute_skill_action vs. decompose_research_query). Description is vague ('Execute deterministic, zero-dependency AI Deep Research & Scientific Consensus operations') and does not explain WHEN to use it or WHAT it returns. Input schema present but parameter 'query_payload' lacks meaningful description ('Input execution payload' is circular). No output schema documented, response structure is hardcoded JSON string, not a typed object. No error handling guidance. Tool appears to be a stub that always returns success without actual implementation.

• Rename tool to 'decompose_research_query' to match the actual capability shown in client.py and follow verb_noun naming convention.
• Expand tool description to 100-200 chars: 'Decompose a complex research inquiry into sub-queries and generate a synthesis plan. Returns decomposition ID, sub-queries, synthesis waves, and plan URL. Use this to break down multihop research tasks.'
• Add parameter description for query_payload: 'The research inquiry to decompose (string, 50-2000 chars). E.g., "Compare geopolitical implications of sodium-ion vs solid-state battery adoption in maritime freight".'
• Document output schema explicitly: {decomposition_id, root_inquiry, sub_queries_generated[], synthesis_dag_waves_count, estimated_sources_needed, query_plan_url}. Include field types and descriptions.
• Add error handling: return structured errors for invalid input (too short/long), rate limits, or service unavailability with actionable recovery guidance.