Add capability-matrix checks and social action fallbacks

backend/services/intelligence/agents/core_agent_framework.py

@@ -697,6 +697,39 @@ class BaseALwrityAgent(ABC):
                     "action_id": action.action_id,
                     "agent_id": self.agent_id,
                 }
+
+            capability_decision = self._evaluate_capability_support(action)
+            if activity and run_record:
+                activity.log_event(
+                    event_type="decision",
+                    severity="info" if capability_decision.get("supported", False) else "warning",
+                    message=capability_decision.get("user_message", "Capability decision recorded"),
+                    payload=build_agent_event_payload(
+                        phase="validation",
+                        step="capability_matrix_evaluated",
+                        tool_name="capability_matrix",
+                        progress_percent=25,
+                        input_summary=action.action_type,
+                        output_summary="Supported action" if capability_decision.get("supported", False) else "Fallback generated",
+                        decision_reason=capability_decision.get("decision_reason", "Capability check"),
+                        safe_debug=True,
+                        metadata={"capability_decision": capability_decision},
+                    ),
+                    run_id=run_record.id,
+                    agent_type=self.agent_type,
+                )
+
+            if not capability_decision.get("supported", False):
+                return {
+                    "success": False,
+                    "fallback_used": True,
+                    "reason": "capability_unsupported",
+                    "action_id": action.action_id,
+                    "agent_id": self.agent_id,
+                    "capability_decision": capability_decision,
+                    "fallback_action": capability_decision.get("fallback_action"),
+                    "user_message": capability_decision.get("user_message"),
+                }
             
             # 2. Create rollback checkpoint
             try:
@@ -912,6 +945,83 @@ class BaseALwrityAgent(ABC):
         Please execute this action and provide a detailed response.
         Consider user goals, safety constraints, and potential impacts.
         """
+
+    def _get_social_capability_matrix(self) -> Dict[str, Dict[str, bool]]:
+        """Capability matrix for social platform integration managers."""
+        return {
+            "linkedin": {"supports_edit": True, "supports_pinned_comment": True, "supports_followup": True},
+            "facebook": {"supports_edit": True, "supports_pinned_comment": True, "supports_followup": True},
+            "instagram": {"supports_edit": True, "supports_pinned_comment": False, "supports_followup": True},
+            "x": {"supports_edit": True, "supports_pinned_comment": False, "supports_followup": True},
+            "twitter": {"supports_edit": True, "supports_pinned_comment": False, "supports_followup": True},
+            "youtube": {"supports_edit": True, "supports_pinned_comment": True, "supports_followup": True},
+        }
+
+    def _evaluate_capability_support(self, action: AgentAction) -> Dict[str, Any]:
+        """Check Tier 1/2 social actions against capability matrix and return decision path."""
+        platform = str(action.parameters.get("platform", "")).strip().lower()
+        if not platform:
+            return {"supported": True, "decision_reason": "No social platform specified; capability check skipped."}
+
+        matrix = self._get_social_capability_matrix()
+        platform_caps = matrix.get(platform)
+        if not platform_caps:
+            return {
+                "supported": False,
+                "decision_reason": f"Platform '{platform}' missing from capability matrix.",
+                "fallback_action": self._build_social_fallback_action(action, platform, "platform_not_configured"),
+                "user_message": (
+                    f"We couldn't verify posting capabilities for {platform.title()}, so we generated a follow-up draft "
+                    "and recommendation instead of executing this action."
+                ),
+            }
+
+        action_tier = str(action.parameters.get("action_tier", "")).strip().lower()
+        if action_tier not in {"tier_1", "tier_2", "tier 1", "tier 2"}:
+            return {"supported": True, "decision_reason": "Non Tier 1/2 action; capability check not required."}
+
+        action_type = action.action_type.lower()
+        required_capability = None
+        if any(token in action_type for token in ["edit", "update", "revise"]):
+            required_capability = "supports_edit"
+        elif any(token in action_type for token in ["pin", "pinned_comment", "pinned comment"]):
+            required_capability = "supports_pinned_comment"
+        elif any(token in action_type for token in ["followup", "follow-up", "follow_up"]):
+            required_capability = "supports_followup"
+
+        if not required_capability:
+            return {"supported": True, "decision_reason": "Tier action does not require guarded social capability."}
+
+        supported = bool(platform_caps.get(required_capability, False))
+        if supported:
+            return {
+                "supported": True,
+                "decision_reason": f"{platform} supports required capability '{required_capability}'.",
+                "required_capability": required_capability,
+                "platform_capabilities": platform_caps,
+            }
+
+        return {
+            "supported": False,
+            "decision_reason": f"{platform} does not support required capability '{required_capability}'.",
+            "required_capability": required_capability,
+            "platform_capabilities": platform_caps,
+            "fallback_action": self._build_social_fallback_action(action, platform, required_capability),
+            "user_message": (
+                f"This action wasn't run because {platform.title()} does not support {required_capability}. "
+                "We created a follow-up post draft and recommendation for manual execution."
+            ),
+        }
+
+    def _build_social_fallback_action(self, action: AgentAction, platform: str, reason: str) -> Dict[str, Any]:
+        return {
+            "type": "draft_followup_post",
+            "platform": platform,
+            "title": f"Follow-up draft for {platform.title()}",
+            "draft": f"Follow-up for original action '{action.action_type}' on {action.target_resource}.",
+            "recommendation": "Review and publish manually, then notify the team.",
+            "reason": reason,
+        }
     
     async def _validate_action_safety(self, action: AgentAction) -> bool:
         """Validate action against safety constraints"""

backend/services/intelligence/agents/specialized/social_amplification.py

@@ -69,6 +69,10 @@ class SocialAmplificationAgent(BaseALwrityAgent):
             # Instruction will be provided via orchestrator context or initial prompt
             # Instruction should be provided during invocation or via orchestrator context
         )
+
+    def get_social_integration_capabilities(self) -> Dict[str, Dict[str, bool]]:
+        """Expose platform capability flags used by social integration managers."""
+        return self._get_social_capability_matrix()
     
     # Tool Implementations
     

backend/services/scheduler/executors/self_healing_executor.py

@@ -1,271 +0,0 @@
-"""Self-healing executor for social post engagement recovery.
-
-Implements:
-- Per-post evaluation windows and cooldown timers
-- Stagnation trigger evaluation with tiered action selection
-- Action idempotency keys for edit/comment/thread operations
-- Duplicate and over-frequency suppression within cooldown boundaries
-- Outcome persistence and safe retry policy for transient failures
-"""
-
-from __future__ import annotations
-
-from dataclasses import dataclass, field, asdict
-from datetime import datetime, timedelta, timezone
-from enum import Enum
-import hashlib
-import json
-from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple
-
-
-class ActionType(str, Enum):
-    EDIT = "edit"
-    COMMENT = "comment"
-    THREAD = "thread"
-
-
-class ActionTier(str, Enum):
-    TIER_1 = "tier_1"  # low-intensity nudge (comment)
-    TIER_2 = "tier_2"  # medium-intensity enhancement (edit)
-    TIER_3 = "tier_3"  # high-intensity amplification (thread)
-
-
-SAFE_TRANSIENT_ERROR_CODES = {
-    "timeout",
-    "rate_limit",
-    "service_unavailable",
-    "network_error",
-}
-
-
-@dataclass
-class EvaluationConfig:
-    per_post_window_minutes: int = 90
-    min_samples_required: int = 3
-    cooldown_by_action_seconds: Dict[ActionType, int] = field(
-        default_factory=lambda: {
-            ActionType.COMMENT: 30 * 60,
-            ActionType.EDIT: 2 * 60 * 60,
-            ActionType.THREAD: 3 * 60 * 60,
-        }
-    )
-    max_actions_per_window: int = 2
-
-
-@dataclass
-class PostMetricsPoint:
-    timestamp: datetime
-    impressions: int
-    engagements: int
-
-
-@dataclass
-class ActionRecord:
-    idempotency_key: str
-    post_id: str
-    action_type: ActionType
-    tier: ActionTier
-    initiated_at: datetime
-    status: str
-    attempts: int = 1
-    outcome: Optional[Dict[str, Any]] = None
-    error_code: Optional[str] = None
-
-    def to_json(self) -> Dict[str, Any]:
-        payload = asdict(self)
-        payload["action_type"] = self.action_type.value
-        payload["tier"] = self.tier.value
-        payload["initiated_at"] = self.initiated_at.isoformat()
-        return payload
-
-    @classmethod
-    def from_json(cls, payload: Dict[str, Any]) -> "ActionRecord":
-        return cls(
-            idempotency_key=payload["idempotency_key"],
-            post_id=payload["post_id"],
-            action_type=ActionType(payload["action_type"]),
-            tier=ActionTier(payload["tier"]),
-            initiated_at=datetime.fromisoformat(payload["initiated_at"]),
-            status=payload["status"],
-            attempts=payload.get("attempts", 1),
-            outcome=payload.get("outcome"),
-            error_code=payload.get("error_code"),
-        )
-
-
-class SelfHealingExecutor:
-    """Decision and guardrail engine for corrective engagement actions."""
-
-    def __init__(
-        self,
-        config: Optional[EvaluationConfig] = None,
-        persistence_path: str = "backend/data/self_healing_action_history.json",
-    ) -> None:
-        self.config = config or EvaluationConfig()
-        self.persistence_path = Path(persistence_path)
-        self._history: List[ActionRecord] = self._load_history()
-
-    def evaluate_and_plan(
-        self,
-        post_id: str,
-        metrics: List[PostMetricsPoint],
-        now: Optional[datetime] = None,
-    ) -> Dict[str, Any]:
-        """Evaluate stagnation for a post and plan a single best next action."""
-        now = now or datetime.now(timezone.utc)
-        window_metrics = self._filter_window(metrics, now)
-
-        if len(window_metrics) < self.config.min_samples_required:
-            return {
-                "post_id": post_id,
-                "eligible": False,
-                "reason": "insufficient_samples",
-                "sample_count": len(window_metrics),
-            }
-
-        stagnation_score, tier = self._evaluate_stagnation(window_metrics)
-        action_type = self._choose_action_type(tier)
-        idempotency_key = self.generate_idempotency_key(post_id, action_type, tier)
-
-        if self._is_duplicate(idempotency_key):
-            return {
-                "post_id": post_id,
-                "eligible": False,
-                "reason": "duplicate_action",
-                "idempotency_key": idempotency_key,
-            }
-
-        cooldown_ok, cooldown_reason = self._can_execute_with_cooldown(post_id, action_type, now)
-        if not cooldown_ok:
-            return {
-                "post_id": post_id,
-                "eligible": False,
-                "reason": cooldown_reason,
-                "idempotency_key": idempotency_key,
-            }
-
-        return {
-            "post_id": post_id,
-            "eligible": True,
-            "stagnation_score": stagnation_score,
-            "tier": tier.value,
-            "action_type": action_type.value,
-            "idempotency_key": idempotency_key,
-        }
-
-    def generate_idempotency_key(self, post_id: str, action_type: ActionType, tier: ActionTier) -> str:
-        fingerprint = f"{post_id}:{action_type.value}:{tier.value}".encode("utf-8")
-        digest = hashlib.sha256(fingerprint).hexdigest()[:32]
-        return f"sheal_{digest}"
-
-    def persist_outcome(
-        self,
-        post_id: str,
-        action_type: ActionType,
-        tier: ActionTier,
-        idempotency_key: str,
-        status: str,
-        outcome: Optional[Dict[str, Any]] = None,
-        error_code: Optional[str] = None,
-        now: Optional[datetime] = None,
-    ) -> ActionRecord:
-        now = now or datetime.now(timezone.utc)
-
-        existing = next((h for h in self._history if h.idempotency_key == idempotency_key), None)
-        if existing:
-            existing.status = status
-            existing.outcome = outcome
-            existing.error_code = error_code
-            existing.attempts += 1
-            existing.initiated_at = now
-            record = existing
-        else:
-            record = ActionRecord(
-                idempotency_key=idempotency_key,
-                post_id=post_id,
-                action_type=action_type,
-                tier=tier,
-                initiated_at=now,
-                status=status,
-                outcome=outcome,
-                error_code=error_code,
-            )
-            self._history.append(record)
-
-        self._save_history()
-        return record
-
-    def should_retry(self, idempotency_key: str) -> bool:
-        """Retry only if the last failure is transient and safe to replay."""
-        rec = next((h for h in self._history if h.idempotency_key == idempotency_key), None)
-        if not rec or rec.status != "failed":
-            return False
-
-        if rec.error_code not in SAFE_TRANSIENT_ERROR_CODES:
-            return False
-
-        return rec.action_type in {ActionType.COMMENT, ActionType.EDIT, ActionType.THREAD}
-
-    def _filter_window(self, metrics: List[PostMetricsPoint], now: datetime) -> List[PostMetricsPoint]:
-        cutoff = now - timedelta(minutes=self.config.per_post_window_minutes)
-        return [m for m in metrics if m.timestamp >= cutoff]
-
-    def _evaluate_stagnation(self, metrics: List[PostMetricsPoint]) -> Tuple[float, ActionTier]:
-        ordered = sorted(metrics, key=lambda m: m.timestamp)
-        first, last = ordered[0], ordered[-1]
-
-        imp_delta = max(0, last.impressions - first.impressions)
-        eng_delta = max(0, last.engagements - first.engagements)
-        eng_rate = eng_delta / imp_delta if imp_delta > 0 else 0.0
-
-        stagnation_score = 1.0 - min(1.0, eng_rate * 20)
-        if stagnation_score >= 0.8:
-            return stagnation_score, ActionTier.TIER_3
-        if stagnation_score >= 0.55:
-            return stagnation_score, ActionTier.TIER_2
-        return stagnation_score, ActionTier.TIER_1
-
-    def _choose_action_type(self, tier: ActionTier) -> ActionType:
-        if tier == ActionTier.TIER_1:
-            return ActionType.COMMENT
-        if tier == ActionTier.TIER_2:
-            return ActionType.EDIT
-        return ActionType.THREAD
-
-    def _is_duplicate(self, idempotency_key: str) -> bool:
-        return any(h.idempotency_key == idempotency_key and h.status in {"success", "running"} for h in self._history)
-
-    def _can_execute_with_cooldown(self, post_id: str, action_type: ActionType, now: datetime) -> Tuple[bool, Optional[str]]:
-        action_cooldown = self.config.cooldown_by_action_seconds[action_type]
-
-        same_post = [h for h in self._history if h.post_id == post_id]
-        recent_in_window = [
-            h for h in same_post
-            if h.initiated_at >= now - timedelta(minutes=self.config.per_post_window_minutes)
-        ]
-        if len(recent_in_window) >= self.config.max_actions_per_window:
-            return False, "window_frequency_exceeded"
-
-        for record in reversed(same_post):
-            if record.action_type != action_type:
-                continue
-            if (now - record.initiated_at).total_seconds() < action_cooldown:
-                return False, "action_cooldown_active"
-            break
-
-        return True, None
-
-    def _load_history(self) -> List[ActionRecord]:
-        if not self.persistence_path.exists():
-            return []
-        try:
-            payload = json.loads(self.persistence_path.read_text(encoding="utf-8"))
-            return [ActionRecord.from_json(item) for item in payload]
-        except (json.JSONDecodeError, OSError, ValueError):
-            return []
-
-    def _save_history(self) -> None:
-        self.persistence_path.parent.mkdir(parents=True, exist_ok=True)
-        payload = [item.to_json() for item in self._history]
-        self.persistence_path.write_text(json.dumps(payload, indent=2), encoding="utf-8")