chore: update runtime logs to use 'LLM enrichment' instead of 'Agent skill'

- agent_handlers.py: 'Agent skill' -> 'LLM enrichment' in all log messages
- skill_registry.py: 'agent skills' -> 'prompt-based skills' in discovery log
- llm_service.py: docstring 'agent skills' -> 'LLM-based enrichment features'

py/routes/handlers/agent_handlers.py

@@ -99,12 +99,12 @@ class AgentHandler:
         # Launch execution in the background
         progress_reporter = AgentProgressReporter()
         logger.info(
-            "Agent skill '%s' starting for %d model(s) in background task",
+            "LLM enrichment '%s' starting for %d model(s) in background task",
             skill_name, len(model_paths),
         )
 
         async def _run() -> None:
-            logger.info("_run background task started for skill '%s'", skill_name)
+            logger.info("Background task started for enrichment '%s'", skill_name)
             try:
                 result = await service.execute_skill(
                     skill_name=skill_name,
@@ -112,11 +112,11 @@ class AgentHandler:
                     progress_callback=progress_reporter,
                 )
                 logger.info(
-                    "Agent skill '%s' finished: success=%s, summary='%s', errors=%s",
+                    "LLM enrichment '%s' finished: success=%s, summary='%s', errors=%s",
                     skill_name, result.success, result.summary, result.errors,
                 )
             except LLMNotConfiguredError as exc:
-                logger.warning("Agent skill '%s' not configured: %s", skill_name, exc)
+                logger.warning("LLM enrichment '%s' not configured: %s", skill_name, exc)
                 await progress_reporter.on_progress(
                     {
                         "type": "agent_progress",
@@ -126,7 +126,7 @@ class AgentHandler:
                     }
                 )
             except Exception as exc:
-                logger.error("Agent skill '%s' failed: %s", skill_name, exc, exc_info=True)
+                logger.error("LLM enrichment '%s' failed: %s", skill_name, exc, exc_info=True)
                 await progress_reporter.on_progress(
                     {
                         "type": "agent_progress",
@@ -138,7 +138,7 @@ class AgentHandler:
 
         # Fire and forget — progress comes via WebSocket
         task = asyncio.create_task(_run())
-        logger.info("Agent skill '%s' background task created (id=%s)", skill_name, task)
+        logger.info("LLM enrichment '%s' background task created (id=%s)", skill_name, task)
 
         return web.json_response(
             {

py/services/agent/skill_registry.py

@@ -141,7 +141,7 @@ class SkillRegistry:
                 logger.warning("Failed to load skill from %s: %s", prompt_file, exc)
 
         self._loaded = True
-        logger.info("Discovered %d agent skills", len(self._skills))
+        logger.info("Discovered %d prompt-based skills", len(self._skills))
 
     def _load_skill_definition(self, path: Path) -> Optional[SkillDefinition]:
         """Parse a prompt definition file's frontmatter into a

py/services/llm_service.py

@@ -187,8 +187,8 @@ _LLM_TIMEOUT = aiohttp.ClientTimeout(total=120)
 class LLMService:
     """Centralized LLM API client.
 
-    All agent skills call LLMs through this service so that BYOK config,
-    retry logic, and error handling live in one place.
+    All LLM-based enrichment features call through this service so
+    that BYOK config, retry logic, and error handling live in one place.
     """
 
     _instance: Optional["LLMService"] = None