fix(tools): decouple runtime from agent runner

src/langbot/pkg/provider/tools/loaders/skill.py

@@ -10,7 +10,6 @@ if typing.TYPE_CHECKING:
     from langbot_plugin.api.entities.events import pipeline_query
 
 ACTIVATED_SKILLS_KEY = '_activated_skills'
-ACTIVATED_SKILL_NAMES_STATE_KEY = 'host.activated_skills'
 PIPELINE_BOUND_SKILLS_KEY = '_pipeline_bound_skills'
 SKILL_MOUNT_PREFIX = '/workspace/.skills'
 _SKILL_MOUNT_PATTERN = re.compile(r'/workspace/\.skills/([A-Za-z0-9_-]+)')
@@ -73,7 +72,8 @@ def register_activated_skill(query: pipeline_query.Query, skill_data: dict) -> N
         activated[skill_name] = skill_data
 
 
-def _normalize_skill_names(value: typing.Any) -> list[str]:
+def normalize_skill_names(value: typing.Any) -> list[str]:
+    """Return a de-duplicated list of non-empty skill names."""
     if not isinstance(value, list):
         return []
 
@@ -85,21 +85,24 @@ def _normalize_skill_names(value: typing.Any) -> list[str]:
     return names
 
 
-def restore_activated_skills_from_state(
+def get_activated_skill_names(query: pipeline_query.Query) -> list[str]:
+    """Return activated skill names for callers that own persistence policy."""
+    return normalize_skill_names(list(get_activated_skills(query).keys()))
+
+
+def restore_activated_skills(
     ap: app.Application,
     query: pipeline_query.Query,
-    state: dict[str, dict[str, typing.Any]],
+    skill_names: typing.Any,
 ) -> list[str]:
-    """Restore persisted activated skill names into Query variables.
+    """Restore caller-provided activated skill names into Query variables.
 
-    The state value stores names only. Full skill metadata is rebuilt from the
-    current pipeline-visible skill cache so removed or unbound skills remain
-    unavailable to native exec/write/edit.
+    Persistence and state scope ownership belong to higher-level flows. This
+    helper only rebuilds current Query state from pipeline-visible skills, so
+    removed or unbound skills stay unavailable to native exec/write/edit.
     """
-    conversation_state = state.get('conversation', {}) if isinstance(state, dict) else {}
-    skill_names = _normalize_skill_names(conversation_state.get(ACTIVATED_SKILL_NAMES_STATE_KEY))
     restored: list[str] = []
-    for skill_name in skill_names:
+    for skill_name in normalize_skill_names(skill_names):
         skill_data = get_visible_skill(ap, query, skill_name)
         if skill_data is None:
             continue
@@ -108,81 +111,6 @@ def restore_activated_skills_from_state(
     return restored
 
 
-def _get_agent_run_authorization(query: pipeline_query.Query) -> dict[str, typing.Any] | None:
-    session = getattr(query, '_agent_run_session', None)
-    if not isinstance(session, dict):
-        return None
-    authorization = session.get('authorization')
-    return authorization if isinstance(authorization, dict) else None
-
-
-def _get_conversation_state_target(query: pipeline_query.Query) -> tuple[str, str, str, dict[str, typing.Any]] | None:
-    session = getattr(query, '_agent_run_session', None)
-    if not isinstance(session, dict):
-        return None
-
-    authorization = _get_agent_run_authorization(query)
-    if authorization is None:
-        return None
-
-    state_policy = authorization.get('state_policy') or {}
-    if not state_policy.get('enable_state', True):
-        return None
-    state_scopes = state_policy.get('state_scopes', ['conversation', 'actor'])
-    if 'conversation' not in state_scopes:
-        return None
-
-    state_context = authorization.get('state_context') or {}
-    scope_keys = state_context.get('scope_keys') or {}
-    scope_key = scope_keys.get('conversation')
-    if not scope_key:
-        return None
-
-    runner_id = str(session.get('runner_id') or 'unknown')
-    binding_identity = str(state_context.get('binding_identity') or 'unknown')
-    return scope_key, runner_id, binding_identity, state_context
-
-
-async def persist_activated_skill(ap: app.Application, query: pipeline_query.Query, skill_name: str) -> bool:
-    """Persist activated skill names for the current AgentRunner conversation.
-
-    Returns False when the call is outside an AgentRunner run or state policy
-    does not expose a conversation scope. The in-memory Query activation still
-    remains valid for the current turn.
-    """
-    target = _get_conversation_state_target(query)
-    if target is None:
-        return False
-
-    persistence_mgr = getattr(ap, 'persistence_mgr', None)
-    if persistence_mgr is None or not hasattr(persistence_mgr, 'get_db_engine'):
-        return False
-
-    from ....agent.runner.persistent_state_store import get_persistent_state_store
-
-    scope_key, runner_id, binding_identity, state_context = target
-    store = get_persistent_state_store(persistence_mgr.get_db_engine())
-    existing_names = _normalize_skill_names(await store.state_get(scope_key, ACTIVATED_SKILL_NAMES_STATE_KEY))
-    if skill_name not in existing_names:
-        existing_names.append(skill_name)
-
-    success, error = await store.state_set(
-        scope_key=scope_key,
-        state_key=ACTIVATED_SKILL_NAMES_STATE_KEY,
-        value=existing_names,
-        runner_id=runner_id,
-        binding_identity=binding_identity,
-        scope='conversation',
-        context=state_context,
-        logger=getattr(ap, 'logger', None),
-    )
-    if not success:
-        logger = getattr(ap, 'logger', None)
-        if logger is not None:
-            logger.warning(f'Failed to persist activated skill "{skill_name}": {error}')
-    return success
-
-
 def parse_skill_mount_path(sandbox_path: str) -> tuple[str | None, str]:
     normalized_path = str(sandbox_path or '/workspace').strip() or '/workspace'
     if normalized_path == SKILL_MOUNT_PREFIX: