Tables are central to business document workflows, but practical table-processing tasks vary substantially in structure, content, and required action. We compare eight ReAct-agent configurations built on the same Qwen3.6-35B-A3B model. The design crosses four tool profiles - Minimal, Search, Spreadsheet, and Full - with the presence or absence of Markdown-based procedural skills. We evaluate the configurations on 40 tasks from company workflows, FinQA, and SpreadsheetBench. Across three complete replicates, comprising 960 agent-task episodes, Full with skills obtains the highest aggregate success rate of 75.0% and a mean score of 0.8061. Full without skills reaches 65.0%, while Spreadsheet without skills reaches 73.3%. Aggregated across tool profiles, skills increase success from 69.4% to 72.3%, but their effect is heterogeneous: negative for Minimal and Spreadsheet and positive for Search and Full. Overall success remains stable across replicates at 70.3%, 70.9%, and 71.3%, although individual configuration results vary more substantially. These findings suggest that procedural guidance is most promising when an agent must coordinate a broad tool environment rather than as a universal augmentation.