fix: validate script_path exists + tell agent to call generate_job_file

Two problems with the prior prepare_submit_job flow:

  1. The agent could pass a script_path that only existed in its own
     context (LLM-generated code not yet on disk) or a path on the host
     filesystem that's invisible inside the container. The new check
     surfaces this as a 400 with a clear remediation hint instead of
     letting spark-submit fail later with an opaque FileNotFoundError -> 500.

  2. The container-isolation issue: any path the agent gives is interpreted
     inside the container. The two ways a file can legitimately exist there
     are (a) generate_job_file(code=...) just wrote it to
     SPARK_EXECUTOR_JOBS_DIR (the default ./data/jobs/ is the only
     gitignored dir that survives restarts), or (b) a host dir was
     mounted via -v. The error message spells both out so an agent can
     self-correct.

Implementation:
  - submit.py: new _check_script_path() that raises ValueError (-> 400)
    when the path is missing, empty, or a directory. Called in both
    prepare_submit_job and confirm_submit_job (defense in depth).
  - prepare_submit_job checks the connection FIRST (KeyError -> 404)
    before the script (ValueError -> 400), so an agent with both problems
    sees the more fundamental 'unknown connection' error first.
  - server.py / requests.py: route description and Pydantic field
    description spell out the generate_job_file pattern so an LLM
    reading the tool schema learns the right next step.

8 new tests; 8 existing tests adjusted to create real files (they used
synthetic /tmp/*.py paths that don't exist).

spark_executor/tools/requests.py

@@ -26,7 +26,18 @@ class SaveConnectionRequest(BaseModel):
 
 class PrepareSubmitJobRequest(BaseModel):
     connection: str
-    script_path: str
+    script_path: str = Field(
+        ...,
+        description=(
+            "Absolute path to the PySpark script inside the container's "
+            "filesystem. Must point at an existing regular file. For "
+            "LLM-generated code, call generate_job_file(code=...) first "
+            "and pass the returned script_path here. For pre-existing "
+            "files on the host, mount them via a docker volume and pass "
+            "the in-container path. Returns 400 with a remediation hint "
+            "if the path is missing or not a file."
+        ),
+    )
     queue: str = "default"
     executor_memory: str = "4G"
     executor_cores: int = 2