feat: add generate_job_file MCP tool (Stage 2 Task 22)

Exposes a single new MCP tool: generate_job_file(code) -> {script_path}.

Wiring follows the Stage 1 conventions (Pydantic body model for the
route, loguru DEBUG/INFO logging, summary+description for the startup
log, MCP arg-pattern via the body model so tools/call roundtrips long
code strings without 422-ing on FastAPI query length limits).

Flow:
  1. LLM calls generate_job_file(code=...)          -> {script_path}
  2. LLM calls prepare_submit_job(connection=...,
                                  script_path=...) -> {pending_id}
  3. User reviews the file + pending record
  4. LLM calls confirm_submit_job(pending_id=...)  -> spark-submit runs

The output directory is SPARK_EXECUTOR_JOBS_DIR (default ./data/jobs/,
gitignored, persists across container restarts via the existing
./data volume mount in docker-compose.yml).

3 new tests:
  - Unit: env-var override, default fallback in tmp cwd
  - Integration: end-to-end body call with a > FastAPI-query-limit code
    string (the canary test that would have caught the Stage 1
    query-params-422 bug)

Live MCP smoke verified: tools/list shows 14 tools (13 from Stage 1 +
the new one), tools/call generate_job_file returns the absolute path
under ./data/jobs/.

spark_executor/tools/generate.py

@@ -0,0 +1,20 @@
+# coding=utf-8
+"""
+@Time   :2026/6/24
+@Author :tao.chen
+"""
+from common.logging import logger
+from spark_executor.core.job_writer import write_job_file
+
+
+def generate_job_file(code: str) -> dict[str, str]:
+    """Write a PySpark code string to disk; return its absolute path.
+
+    Use the returned path as the `script_path` argument of prepare_submit_job.
+    The output directory is controlled by the SPARK_EXECUTOR_JOBS_DIR env var
+    (default: ./data/jobs/).
+    """
+    logger.debug(f"generate_job_file enter code_bytes={len(code)}")
+    path = write_job_file(code)
+    logger.info(f"generate_job_file ok script_path={path}")
+    return {"script_path": path}

spark_executor/tools/requests.py

@@ -48,3 +48,14 @@ class GetJobLogsRequest(BaseModel):
 
 class ConnectionNameRequest(BaseModel):
     name: str
+
+
+class GenerateJobFileRequest(BaseModel):
+    code: str = Field(
+        ...,
+        description=(
+            "Full PySpark source code to write to disk. Will be passed verbatim "
+            "to spark-submit after the agent calls prepare_submit_job on the "
+            "returned path."
+        ),
+    )