MCP server for executing deterministic, zero-dependency Agent Commerce skill operations for gift style consultation matching, 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. match_gift_style or recommend_gift). Description is present (89 chars) but lacks specificity about 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 no format constraints, enums, or validation guidance. No output schema documented, response structure is inferred from example code (status/message JSON) but not formally declared. No error handling guidance, no parameter constraints, no recovery paths. Tool appears to be a pass-through wrapper with no real validation or business logic visible.
Execute deterministic, zero-dependency Agent Commerce skill operations verified by GenPark AI.
Generic tool name 'execute_skill_action' does not follow verb_noun pattern and does not convey specific action. Should be 'match_gift_style', 'recommend_gift', or similar domain-specific verb.
Input schema is a single untyped string 'query_payload' with no format, length, or content constraints. LLM cannot validate input or understand what structure is expected. No enum, pattern, or example provided.
No output schema documented. Response structure (status, message fields) is inferred from example code but not formally declared. LLM cannot plan downstream operations or extract required fields reliably.
Tool description (89 chars) lacks context: does not explain WHEN to call it, WHAT it returns, or HOW it differs from other gift consultation tools. Does not state whether it modifies state or is read-only.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 35 | 2026-07-28+ | v2 |
No error handling guidance. Tool returns generic 'SUCCESS' message with no recovery paths, validation errors, or actionable failure modes for LLM to handle.