A developer is debugging a production issue where Claude's function calling behavior is inconsistent. For the same input, Claude sometimes calls tool A first, sometimes tool B first, even with temperature: 0. The tools are: search_knowledge_base(query) and get_user_profile(user_id). The task is: 'Find the user's account history and any relevant support articles.' The developer expects a deterministic sequence: get_user_profile first, then search_knowledge_base. How should this be enforced architecturally?

The most robust architectural enforcement of tool call sequence is removing unavailable tools from the tools array. If search_knowledge_base is not in the tools list on the first call, Claude literally cannot call it — the sequence is enforced by API design, not by model behavior. After get_user_profile returns its result, search_knowledge_base is added for the second call. This approach is deterministic regardless of model behavior, temperature settings, or prompt phrasing. Option B (tool_choice forcing) correctly enforces the first tool but uses auto for the second — if the second call's context makes Claude want to call get_user_profile again, it can. Tool_choice: auto doesn't enforce that search_knowledge_base is called next. Option C (prompt sequencing) is a reasonable soft approach but not architecturally robust — model behavior with multiple available tools can deviate from textual sequence instructions, especially under edge-case inputs. Option A is factually incorrect: temperature and top_p affect sampling randomness but tool selection in agentic contexts is not purely sampling-based — multiple valid orderings may have similar likelihoods.