Single tool 'execute_skill_action' has a basic description (89 chars) and minimal input schema. The description lacks WHAT the tool does operationally, WHEN to use it, and what it returns. Parameter 'query_payload' is a generic string with no format guidance, constraints, or examples of valid payloads. No output schema is documented, the response structure is hardcoded JSON but never formally specified. No error handling guidance. The tool name uses a generic verb ('execute') rather than a domain-specific action. No parameter validation rules, no idempotency guarantees, no security considerations. This is a stub implementation masquerading as a production tool.

• Rename tool to a domain-specific verb: 'rank_code_completions' or 'synthesize_code_snippet', something that conveys the actual operation.
• Expand description to 100-200 chars: 'Ranks candidate code completions using AST syntax validation and contextual relevance scoring. Input: cursor prefix/suffix code and candidate snippets. Output: ranked candidates with scores and latency. Use this to select the best code completion for a given context.'
• Replace 'query_payload' string parameter with structured inputs: 'cursor_prefix_code' (string), 'cursor_suffix_code' (string), 'candidate_completions' (array of strings). Add descriptions for each.
• Document output schema explicitly: { 'ranking_id': string, 'ranked_candidates': [{ 'snippet': string, 'ast_syntax_valid': boolean, 'contextual_relevance_score': number (0-1), 'latency_ms': number }], 'top_recommendation': string, 'inference_latency_ms': number }
• Add error handling: return structured errors with actionable guidance. E.g., 'Invalid syntax in cursor_prefix_code: expected valid Python. Check for unclosed brackets or quotes.'