fix(usage): read top-level Anthropic cache fields from OAI-compatible proxies

Port from cline/cline#10266.

When OpenAI-compatible proxies (OpenRouter, Vercel AI Gateway, Cline)
route Claude models, they sometimes surface the Anthropic-native cache
counters (`cache_read_input_tokens`, `cache_creation_input_tokens`) at
the top level of the `usage` object instead of nesting them inside
`prompt_tokens_details`. Our chat-completions branch of
`normalize_usage()` only read the nested `prompt_tokens_details` fields,
so those responses:

- reported `cache_write_tokens = 0` even when the model actually did a
  prompt-cache write,
- reported only some of the cache-read tokens when the proxy exposed them
  top-level only,
- overstated `input_tokens` by the missed cache-write amount, which in
  turn made cost estimation and the status-bar cache-hit percentage wrong
  for Claude traffic going through these gateways.

Now the chat-completions branch tries the OpenAI-standard
`prompt_tokens_details` first and falls back to the top-level
Anthropic-shape fields only if the nested values are absent/zero. The
Anthropic and Codex Responses branches are unchanged.

Regression guards added for three shapes: top-level write + nested read,
top-level-only, and both-present (nested wins).

agent/usage_pricing.py

@@ -533,10 +533,22 @@ def normalize_usage(
         prompt_total = _to_int(getattr(response_usage, "prompt_tokens", 0))
         output_tokens = _to_int(getattr(response_usage, "completion_tokens", 0))
         details = getattr(response_usage, "prompt_tokens_details", None)
+        # Primary: OpenAI-style prompt_tokens_details. Fallback: Anthropic-style
+        # top-level fields that some OpenAI-compatible proxies (OpenRouter, Vercel
+        # AI Gateway, Cline) expose when routing Claude models — without this
+        # fallback, cache writes are undercounted as 0 and cache reads can be
+        # missed when the proxy only surfaces them at the top level.
+        # Port of cline/cline#10266.
         cache_read_tokens = _to_int(getattr(details, "cached_tokens", 0) if details else 0)
+        if not cache_read_tokens:
+            cache_read_tokens = _to_int(getattr(response_usage, "cache_read_input_tokens", 0))
         cache_write_tokens = _to_int(
             getattr(details, "cache_write_tokens", 0) if details else 0
         )
+        if not cache_write_tokens:
+            cache_write_tokens = _to_int(
+                getattr(response_usage, "cache_creation_input_tokens", 0)
+            )
         input_tokens = max(0, prompt_total - cache_read_tokens - cache_write_tokens)
 
     reasoning_tokens = 0