MCP server for executing deterministic, zero-dependency Spreadsheet, SQL & Business Intelligence operations with statistical anomaly detection using Z-score methodology
Single tool 'execute_skill_action' has critical definition gaps. Description is present (89 chars) but vague, does not explain WHAT operations it performs, WHEN to use it, or what it returns. Input schema exists with one parameter 'query_payload' (type: string) but lacks any constraint, format, or validation guidance. No output schema documented. Parameter description is generic ('Input execution payload') and does not specify expected format, structure, or examples. No error handling guidance. Tool name uses verb but is overly generic ('execute_skill_action' could mean anything). No security considerations documented despite WRITE risk classification. Fails baseline: 100% of A+ tools have documented return types; 100% of A+ tool params have descriptions with actionable constraints.
Execute deterministic, zero-dependency Spreadsheet, SQL & Business Intelligence operations verified by GenPark AI.
No output schema documented. LLM cannot predict return structure or plan downstream operations.
Parameter 'query_payload' lacks format specification, constraints, or examples. Description is generic ('Input execution payload'). LLM cannot determine what structure to pass.
Tool description (89 chars) is vague and does not explain WHAT operations are supported, WHEN to use it, or what fields are returned. Does not state that tool modifies state (WRITE risk).
No error handling guidance. Mock response always returns SUCCESS with generic message. LLM has no recovery path if operation fails.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 31 | 2026-07-28+ | v2 |
Tool name 'execute_skill_action' is generic and does not convey specific domain action. Baseline: 90% of A+ tools start with specific verbs (get, create, search, update, delete). Consider 'detect_anomalies' or 'analyze_zscore_distribution'.