MCP server for generating interactive presentation slide decks with adaptive card layouts, embedded charts, and brand palette application
Critical failures across all dimensions. The single tool 'execute_skill_action' has no visible input schema, no parameter descriptions, and a generic 1-line description (28 chars). The mcp_server.py file shows only a hardcoded JSON response with no actual tool registration, schema definition, or parameter handling. Tool definitions are inferred from the name alone, not explicitly registered. No error handling, no output schema documentation, and no evidence of input validation. This is a stub implementation, not a functional MCP server.
Execute adaptive presentation slide card generation skill
No input schema visible for execute_skill_action. Tool registration shows only a name string in a hardcoded JSON response, not a proper MCP tool definition with inputSchema.
Tool description is generic and too short (28 chars: 'Execute adaptive presentation slide card generation skill'). Does not explain WHAT the tool does, WHEN to use it, or WHAT it returns. Fails pattern:tool-description baseline of 34-392 chars.
No parameter descriptions visible. The client.py shows parameters like 'pitch_topic' and 'target_slide_cards' but the MCP server does not expose these as tool parameters with types or descriptions. LLM cannot infer parameter meaning.
No output schema documented. The client.py returns a dict with fields like 'deck_card_id', 'topic', 'slide_cards_generated_count', etc., but the MCP server does not declare this structure. LLM cannot plan downstream tool calls or extract data reliably.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 27 | 2026-07-28+ | v2 |
Tool definition is inferred, not explicitly registered. The mcp_server.py prints a hardcoded JSON response with 'supported_tools' as a string array, not a proper MCP tools/list response with full tool definitions including inputSchema.