Drop kimi-k2-thinking from the catalog; remove temporary e2e trigger

- Moonshot serves newer platform accounts exactly one model, kimi-k3:
  K2-era ids and the kimi-latest alias return resource_not_found_error
  on both API surfaces (verified live 2026-07-21). Drop kimi-k2-thinking
  from the kimi_api catalog entry and the pricing defaults so the
  dashboard doesn't advertise a model that 404s; grandfathered accounts
  can still type K2 ids on the provider's model rows.
- Remove the temporary push trigger from agent-network-e2e.yml now that
  the branch validated green (run #76); nightly + workflow_dispatch
  remain.
- Remove CLAUDE.md from the repository.

proxy/internal/llm/pricing/defaults_pricing.yaml

@@ -163,15 +163,13 @@ openai:
 
   # Kimi / Moonshot AI (kimi_api) — OpenAI-compatible /v1 endpoint. Moonshot
   # reports cache hits OpenAI-style when present; cached input is 10% of
-  # input for K3 ($0.30 vs $3.00 per MTok) and $0.15/MTok for K2 Thinking.
+  # input ($0.30 vs $3.00 per MTok). kimi-k3 is the only model the platform
+  # serves newer accounts (K2-era ids and kimi-latest 404), matching the
+  # management catalog.
   kimi-k3:
     input_per_1k: 0.003
     output_per_1k: 0.015
     cached_input_per_1k: 0.0003
-  kimi-k2-thinking:
-    input_per_1k: 0.0006
-    output_per_1k: 0.0025
-    cached_input_per_1k: 0.00015
 
 anthropic:
   # Claude 4.x family — cache reads ≈10% of input, cache writes ≈125% of input.
@@ -220,7 +218,7 @@ anthropic:
 
   # Kimi / Moonshot AI (kimi_api) via the Anthropic-compatible endpoint
   # (/anthropic/v1/messages — the official Claude Code setup). Same rates
-  # as the OpenAI-shape entries above. "kimi-k3[1m]" is the model id some
+  # as the OpenAI-shape entry above. "kimi-k3[1m]" is the model id some
   # Claude Code guides set for the 1M-context alias; priced identically so
   # cost metering doesn't silently skip those requests.
   kimi-k3:
@@ -231,10 +229,6 @@ anthropic:
     input_per_1k: 0.003
     output_per_1k: 0.015
     cache_read_per_1k: 0.0003
-  kimi-k2-thinking:
-    input_per_1k: 0.0006
-    output_per_1k: 0.0025
-    cache_read_per_1k: 0.00015
 
 bedrock:
   # AWS Bedrock model ids, normalised by the request parser (cross-region