Make provider fixtures deterministic and sanitize recorded machine data

• Status: Todo
• Kind: Chore
• Authors: jp
• Date: 2026-08-21
• Label: domain=llm
• Label: package=jp_llm
• Label: type=task

Several fixtures contain avoidable nondeterminism or local machine data:

• The common tool prompt asks the model to provide arbitrary arguments.
• banana.jpg depicts an apple and the test uses a substring assertion.
• Every generic OpenAI fixture uses the same conversation timestamp and prompt-cache key.
• llama.cpp cassettes record /Users/jean/....
• Other recorded fixtures contain host names, UUIDs, process IDs, and absolute paths.

Acceptance criteria:

• Replace the arbitrary tool prompt with separate deterministic scalar, array, default, and nested-value cases.
• Rename the image fixture to match its content and compare the normalized answer exactly.
• Give each cassette a fixed distinct conversation identity while keeping all turns in one cassette on the same identity.
• Extend fixture post-processing to normalize user paths, host names, device UUIDs, process IDs, and timestamps when those values are not under test.
• Add a fixture lint test that rejects common absolute home-directory patterns and known secret header/query fields.