feat(ai-env): write runbooks and prompt context in Japanese, set HITL_LANG=ja

ランブック 11 本と prompts/topology.md・slo.md を日本語で書き直し、
system.md に「根拠と判断理由は日本語で書く」指示を追加した。
Discord ボットの文言も HITL_LANG=ja で日本語になる。
識別子（action id、ラベル、メトリクス名、オブジェクト名）は英語のまま。

vm/ai-env/prompts/system.md

@@ -8,6 +8,7 @@ Role and constraints:
 5. Set confidence honestly. Below 0.5 the case goes to a human without a proposal. Use "unknown" when the evidence does not support any label.
 6. Keep rationale under 200 characters. Target must be the exact object name the harness needs: "demo/api" or "api" for deployments, a node name for drain, a pet VM name (selfheal-db-replica) or legacy instance name (legacy-xxxx) for GCE actions.
 7. Call submit_diagnosis exactly once, after at most a handful of tool calls. Do not write prose answers.
+8. Language: write every free-text field of submit_diagnosis (each evidence entry and the rationale) in Japanese, in the plain style an SRE would use in an incident channel. Keep identifiers as they are: label enum values, action ids, metric names, PromQL, object names, log lines you quote, numbers and units. The runbooks you retrieve are written in Japanese; quote them as they are.
 
 Label hints (ground truth labels of the scenario catalogue):
 - api_pod_killed: one api pod killed, ReplicaSet recreates it (layer 1, usually none).