MCP server for executing deterministic, zero-dependency Merchant Agent skill operations for dynamic pricing and elasticity optimization, verified by GenPark AI.
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. optimize_price or calculate_elasticity). Description is present (89 chars) but lacks actionable context: does not explain WHEN to use it, what it returns, or how it differs from other tools. Input schema exists but is severely underdeveloped: single string parameter 'query_payload' with minimal description ('Input execution payload for this skill') provides no guidance on format, structure, or valid values. No output schema documented, LLM cannot predict response structure. No error handling guidance. Tool appears to be a pass-through wrapper with no real validation or structured behavior.
Execute deterministic, zero-dependency Merchant Agent skill operations verified by GenPark AI.
Generic tool name 'execute_skill_action' does not convey specific action. Should be verb_noun pattern like 'optimize_price_elasticity' or 'calculate_elasticity_impact' to help LLM understand intent without reading description.
Input parameter 'query_payload' is a free-form string with no schema, format, or structure guidance. LLM cannot determine what to pass. Should define expected JSON structure, required fields, and constraints.
No output schema documented. Tool returns JSON with 'status' and 'message' fields, but LLM has no way to know this. Must document return type, field names, and types for downstream tool chaining.
Tool description (89 chars) lacks context: does not explain what 'Merchant Agent skill operations' means, when to call it, what it returns, or how it differs from other tools. Should be 50-200 chars with clear WHAT/WHEN/RETURN guidance.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 33 | 2026-07-28+ | v2 |
No error handling or recovery guidance. If tool fails, LLM receives only 'status: SUCCESS' or implicit failure with no actionable next steps. Must categorize errors and guide recovery.