fix(llm): read input tokens from the frame that carries them

The first judge-spend rows recorded by 248948c came back with input_tokens = 0
on both passes of mission 01a09dfc — 7 and 9 requests, 5940 and 2109 output
tokens, and nothing on the side that actually empties the plan. Probed z.ai's
Anthropic-compatible stream directly: `message_start` carries
`"input_tokens": 0`, and the real figure arrives in `message_delta.usage`
beside output_tokens. Anthropic proper does it the other way round, which is
the shape the parser was written for.

A nonzero figure in the delta now wins; otherwise the start's figure stands,
so the Anthropic path is byte-for-byte unchanged. The decision is a pure
function with the three shapes as its test — including a delta that says 0,
which must not erase what the start said.

Co-Authored-By: Claude Opus 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01WZb5A2kfVfjpdwSochkuHz

crates/cm-llm/src/anthropic.rs

@@ -242,6 +242,14 @@ impl LlmProvider for AnthropicProvider {
                             data["message"]["usage"]["input_tokens"].as_u64().unwrap_or(0) as u32;
                     }
                     "message_delta" => {
+                        // Anthropic reports input_tokens in `message_start`;
+                        // z.ai's Anthropic-compatible endpoint sends 0 there and
+                        // the real count here, beside output_tokens (measured
+                        // 2026-09-14: start `input_tokens: 0`, delta
+                        // `input_tokens: 14`). Prefer the delta's figure when
+                        // it carries one — the judge's input, which is the
+                        // number that empties a plan, read as zero until then.
+                        input_tokens = input_tokens_after_delta(input_tokens, &data["usage"]);
                         if let Some(out) = data["usage"]["output_tokens"].as_u64() {
                             yield LlmEvent::Usage {
                                 input_tokens,
@@ -266,10 +274,38 @@ impl LlmProvider for AnthropicProvider {
     }
 }
 
+/// The input-token figure to report once a `message_delta` has arrived.
+///
+/// `start` is what `message_start` said. Anthropic puts the real count there
+/// and nothing in the delta; z.ai's Anthropic-compatible endpoint puts 0 there
+/// and the real count in the delta's `usage` (measured 2026-09-14). A nonzero
+/// delta figure wins; anything else keeps what `message_start` said, so the
+/// Anthropic path is unchanged.
+fn input_tokens_after_delta(start: u32, delta_usage: &serde_json::Value) -> u32 {
+    match delta_usage["input_tokens"].as_u64() {
+        Some(n) if n > 0 => n as u32,
+        _ => start,
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
 
+    /// z.ai reports input in the delta; Anthropic reports it at the start.
+    /// Before this the judge's input tokens — the number that empties a
+    /// plan — read as zero on every GLM verdict.
+    #[test]
+    fn input_tokens_come_from_whichever_frame_carries_them() {
+        use serde_json::json;
+        // z.ai shape: start says 0, delta says 14.
+        assert_eq!(input_tokens_after_delta(0, &json!({"input_tokens": 14, "output_tokens": 16})), 14);
+        // Anthropic shape: start said 812, delta has no input figure.
+        assert_eq!(input_tokens_after_delta(812, &json!({"output_tokens": 40})), 812);
+        // A delta that explicitly says 0 must not erase the start's figure.
+        assert_eq!(input_tokens_after_delta(812, &json!({"input_tokens": 0, "output_tokens": 40})), 812);
+    }
+
     #[test]
     fn setup_tokens_are_distinguished_from_api_keys() {
         assert!(is_setup_token("sk-ant-oat01-abc"));