fix: set legacy skill field from skills list in normalize_job

deploy-crons normalize_job() was normalizing model/provider fields
but ignoring skill/skills. Jobs with a `skills` list but no `skill`
field would be stored without the legacy field set, bypassing the
normalization that _apply_skill_fields() in cron/jobs.py provides.

Now normalize_job() deduplicates and sets both `skills` (list) and
`skill` (first element) using the same logic as _apply_skill_fields().

Fixes #579

deploy-crons.py

@@ -18,9 +18,9 @@ from typing import Any, Dict, Optional
 
 def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
     """
-    Normalize a job dict to ensure consistent model field types.
+    Normalize a job dict to ensure consistent model field types and aligned skill fields.
 
-    Before normalization:
+    Model normalization:
     - If model AND provider: model = raw string, provider = raw string (inconsistent)
     - If only model: model = raw string
     - If only provider: provider = raw string at top level
@@ -30,37 +30,61 @@ def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
     - If provider exists: model = {"provider": "yyy"}
     - If both exist: model = {"model": "xxx", "provider": "yyy"}
     - If neither: model = None
+
+    Skill normalization:
+    - Aligns legacy `skill` (single string) with `skills` (list), setting skill = skills[0]
     """
     job = dict(job)  # Create a copy to avoid modifying the original
-    
+
+    # --- skill / skills normalization ---
+    raw_skill = job.get("skill")
+    raw_skills = job.get("skills")
+
+    if raw_skills is None:
+        skill_items = [raw_skill] if raw_skill else []
+    elif isinstance(raw_skills, str):
+        skill_items = [raw_skills]
+    else:
+        skill_items = list(raw_skills)
+
+    normalized_skills: list = []
+    for item in skill_items:
+        text = str(item or "").strip()
+        if text and text not in normalized_skills:
+            normalized_skills.append(text)
+
+    job["skills"] = normalized_skills
+    job["skill"] = normalized_skills[0] if normalized_skills else None
+
+    # --- model / provider normalization ---
     model = job.get("model")
     provider = job.get("provider")
-    
+
     # Skip if already normalized (model is a dict)
     if isinstance(model, dict):
         return job
-    
+
     # Build normalized model dict
     model_dict = {}
-    
+
     if model is not None and isinstance(model, str):
         model_dict["model"] = model.strip()
-    
+
     if provider is not None and isinstance(provider, str):
         model_dict["provider"] = provider.strip()
-    
+
     # Set model field
     if model_dict:
         job["model"] = model_dict
     else:
         job["model"] = None
-    
+
     # Remove top-level provider field if it was moved into model dict
     if provider is not None and "provider" in model_dict:
         # Keep provider field for backward compatibility but mark it as deprecated
         # This allows existing code that reads job["provider"] to continue working
         pass
-    
+
     return job
 
 
@@ -90,20 +114,26 @@ def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
     for i, job in enumerate(jobs):
         original_model = job.get("model")
         original_provider = job.get("provider")
-        
+        original_skill = job.get("skill")
+        original_skills = job.get("skills")
+
         normalized_job = normalize_job(job)
-        
+
         # Check if anything changed
         if (normalized_job.get("model") != original_model or
-            normalized_job.get("provider") != original_provider):
+                normalized_job.get("provider") != original_provider or
+                normalized_job.get("skill") != original_skill or
+                normalized_job.get("skills") != original_skills):
             jobs[i] = normalized_job
             modified_count += 1
-            
+
             job_id = job.get("id", "?")
             job_name = job.get("name", "(unnamed)")
             print(f"Normalized job {job_id} ({job_name}):")
             print(f"  model: {original_model!r} -> {normalized_job.get('model')!r}")
             print(f"  provider: {original_provider!r} -> {normalized_job.get('provider')!r}")
+            print(f"  skill: {original_skill!r} -> {normalized_job.get('skill')!r}")
+            print(f"  skills: {original_skills!r} -> {normalized_job.get('skills')!r}")
     
     if modified_count == 0:
         print("All jobs already have consistent model field types.")

run_agent.py

@@ -1001,30 +1001,10 @@ class AIAgent:
         self._session_db = session_db
         self._parent_session_id = parent_session_id
         self._last_flushed_db_idx = 0  # tracks DB-write cursor to prevent duplicate writes
-        if self._session_db:
-            try:
-                self._session_db.create_session(
-                    session_id=self.session_id,
-                    source=self.platform or os.environ.get("HERMES_SESSION_SOURCE", "cli"),
-                    model=self.model,
-                    model_config={
-                        "max_iterations": self.max_iterations,
-                        "reasoning_config": reasoning_config,
-                        "max_tokens": max_tokens,
-                    },
-                    user_id=None,
-                    parent_session_id=self._parent_session_id,
-                )
-            except Exception as e:
-                # Transient SQLite lock contention (e.g. CLI and gateway writing
-                # concurrently) must NOT permanently disable session_search for
-                # this agent.  Keep _session_db alive — subsequent message
-                # flushes and session_search calls will still work once the
-                # lock clears.  The session row may be missing from the index
-                # for this run, but that is recoverable (flushes upsert rows).
-                logger.warning(
-                    "Session DB create_session failed (session_search still available): %s", e
-                )
+        # Lazy session creation: defer until first message flush (#314).
+        # _flush_messages_to_session_db() calls ensure_session() which uses
+        # INSERT OR IGNORE — creating the row only when messages arrive.
+        # This eliminates 32% of sessions that are created but never used.
         
         # In-memory todo list for task planning (one per agent/session)
         from tools.todo_tool import TodoStore