feat(skill-learning): merge plugin skill updates

app-instance/backend/beaver/skills/learning/synthesizer.py

@@ -41,6 +41,55 @@ class SkillDraftSynthesizer:
     ) -> dict[str, Any]:
         return await self._synthesize(candidate, evidence_packet, provider, model, "merge", base_skill=base_skill)
 
+    async def synthesize_plugin_update(
+        self,
+        candidate: SkillLearningCandidate,
+        evidence_packet: EvidencePacket,
+        provider: LLMProvider,
+        model: str,
+        *,
+        old_upstream: dict[str, Any],
+        current_local: dict[str, Any],
+        new_upstream: dict[str, Any],
+    ) -> dict[str, Any]:
+        prompt = self._build_plugin_update_prompt(
+            candidate,
+            evidence_packet,
+            old_upstream=old_upstream,
+            current_local=current_local,
+            new_upstream=new_upstream,
+        )
+        response = await provider.chat(
+            messages=[
+                {
+                    "role": "system",
+                    "content": (
+                        "You merge Beaver plugin skill updates. Return JSON only with keys: "
+                        "frontmatter, content, change_reason, preserved_local_sections, "
+                        "adopted_upstream_sections, resolved_conflicts, dropped_sections. "
+                        "Preserve valid local learning, adopt upstream fixes and safety changes, "
+                        "do not concatenate duplicate sections, and list every intentional drop."
+                    ),
+                },
+                {"role": "user", "content": prompt},
+            ],
+            tools=None,
+            model=model,
+            max_tokens=4096,
+            temperature=0,
+        )
+        payload = self._parse_plugin_update_payload(response.content or "")
+        if payload:
+            return payload
+        fallback = self._fallback_payload(candidate, evidence_packet, "plugin_update")
+        return {
+            **fallback,
+            "preserved_local_sections": [],
+            "adopted_upstream_sections": [],
+            "resolved_conflicts": [],
+            "dropped_sections": [],
+        }
+
     async def _synthesize(
         self,
         candidate: SkillLearningCandidate,
@@ -119,6 +168,28 @@ class SkillDraftSynthesizer:
             + "\nThe JSON may include preserved_sections, changed_sections, and dropped_sections arrays."
         )
 
+    @staticmethod
+    def _build_plugin_update_prompt(
+        candidate: SkillLearningCandidate,
+        evidence_packet: EvidencePacket,
+        *,
+        old_upstream: dict[str, Any],
+        current_local: dict[str, Any],
+        new_upstream: dict[str, Any],
+    ) -> str:
+        return (
+            f"Candidate kind: {candidate.kind}\n"
+            f"Reason: {candidate.reason}\n"
+            f"Task summaries:\n- " + "\n- ".join(evidence_packet.task_summaries or ["No historical run evidence."])
+            + "\n\nOLD UPSTREAM (merge base B):\n"
+            + str(old_upstream.get("content") or "")
+            + "\n\nCURRENT LOCAL (Beaver learned version L):\n"
+            + str(current_local.get("content") or "")
+            + "\n\nNEW UPSTREAM (plugin update U):\n"
+            + str(new_upstream.get("content") or "")
+            + "\n\nReturn JSON only. Preserve useful CURRENT LOCAL learning and adopt important NEW UPSTREAM changes."
+        )
+
     @staticmethod
     def _parse_payload(content: str) -> dict[str, Any]:
         cleaned = content.strip()
@@ -145,6 +216,33 @@ class SkillDraftSynthesizer:
             "dropped_sections": _coerce_string_list(payload.get("dropped_sections")),
         }
 
+    @staticmethod
+    def _parse_plugin_update_payload(content: str) -> dict[str, Any]:
+        cleaned = content.strip()
+        if cleaned.startswith("```"):
+            lines = cleaned.splitlines()
+            if len(lines) >= 3 and lines[0].startswith("```") and lines[-1].startswith("```"):
+                cleaned = "\n".join(lines[1:-1]).strip()
+        try:
+            payload = json.loads(cleaned)
+        except json.JSONDecodeError:
+            return {}
+        if not isinstance(payload, dict):
+            return {}
+        frontmatter = payload.get("frontmatter")
+        content_value = payload.get("content")
+        if not isinstance(frontmatter, dict) or not isinstance(content_value, str):
+            return {}
+        return {
+            "frontmatter": frontmatter,
+            "content": content_value.strip(),
+            "change_reason": str(payload.get("change_reason") or ""),
+            "preserved_local_sections": _coerce_string_list(payload.get("preserved_local_sections")),
+            "adopted_upstream_sections": _coerce_string_list(payload.get("adopted_upstream_sections")),
+            "resolved_conflicts": _coerce_string_list(payload.get("resolved_conflicts")),
+            "dropped_sections": _coerce_string_list(payload.get("dropped_sections")),
+        }
+
     @staticmethod
     def _normalize_payload(payload: dict[str, Any], evidence_packet: EvidencePacket) -> dict[str, Any]:
         frontmatter = normalize_skill_frontmatter(