Single tool with minimal definition quality. Tool name 'execute_skill_action' is generic and does not follow verb_noun pattern (should be 'parse_table_bbox' or similar). Description is 156 chars but vague, does not explain WHAT the tool does operationally, WHEN to use it, or what it returns. Input schema has only one parameter ('query_payload' as free-form string) with no type constraints, enums, or validation hints. No output schema documented, LLM cannot predict response structure. No error handling guidance. Tool appears to be a pass-through echo rather than implementing the actual PDF table parsing logic visible in client.py.

• Rename tool to 'parse_table_bbox' or 'reconstruct_table_from_bbox' to clearly signal the operation and follow verb_noun convention.
• Rewrite description to: 'Reconstruct structured tabular data from unstructured 2D bounding boxes. Accepts cell coordinates (top, left, width, height, text) and returns headers, records, and column count. Use when extracting tables from PDF vision output.'
• Define input schema with structured fields: cells (array of {text, top, left, width, height}), y_tolerance (number, default 6.0), col_tolerance (number, default 12.0). Add descriptions for each field.
• Document output schema: {total_rows: number, column_count: number, headers: array of strings, records: array of objects}. Include field descriptions so LLM knows what to expect.
• Implement the tool to actually call PDFComplexMergedTableBboxParser.reconstruct_table() instead of echoing the query. Wire the client.py logic into the MCP handler.