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MCP server for executing deterministic, zero-dependency AI Video & Generative Media Repurposing operations verified by GenPark AI, specifically for analyzing silence cadence and generating jumpcut timecodes in video content.
Single tool with minimal definition quality. Tool name 'execute_skill_action' is generic and violates verb_noun clarity (pattern:tool). Description is 127 chars but lacks WHAT/WHEN/WHY context required for LLM selection. Input schema present but parameter 'query_payload' has only a 44-char description, insufficient for LLM reasoning. No output schema documented. No error handling guidance. Tool appears to be a catch-all wrapper rather than a focused, composable operation. No parameter validation, constraints, or recovery paths.
Execute deterministic, zero-dependency AI Video & Generative Media Repurposing operations verified by GenPark AI.
Generic tool name 'execute_skill_action' lacks action clarity. Does not follow verb_noun pattern. LLM cannot infer intent from name alone.
Parameter 'query_payload' is a free-form string with no format constraints, enums, or validation rules. LLM cannot determine what structure or content is expected.
No output schema documented. Tool returns hardcoded JSON string with 'status' and 'message' fields, but LLM has no way to know what fields to expect or how to parse results.
Tool description lacks WHAT/WHEN/WHY context. Does not explain when to call this vs other tools, what prerequisites exist, or what the actual operation does beyond 'execute deterministic operations'.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 37 | 2026-07-28+ | v2 |
No error handling or recovery guidance. Hardcoded success response provides no path for LLM to handle failures, retries, or invalid inputs.