feat: implement configurable Xingbang risk agent on mini-openclaw core

backend/tools/risk_task_tools.py

@@ -0,0 +1,35 @@
+"""Tools scoped to an immutable authorized risk run, not the production database."""
+import json
+from copy import deepcopy
+from langchain_core.tools import tool
+
+
+def create_risk_tools(context, evidence, native_skills):
+    snapshot = deepcopy(context)
+    sources = deepcopy(evidence)
+    skills = deepcopy(native_skills)
+
+    @tool
+    def list_data_cards() -> str:
+        """List authorized peer data-card snapshots available for this risk task."""
+        return json.dumps([{"index":i,"name":d["card"],"version":d["version"],"records":len(d["records"])} for i,d in enumerate(snapshot.get("peer_datasets",[]))],ensure_ascii=False)
+
+    @tool
+    def read_data_card(index: int) -> str:
+        """Read one authorized data-card snapshot, including periods and raw evidence."""
+        cards = snapshot.get("peer_datasets", [])
+        if index < 0 or index >= len(cards):
+            return json.dumps({"error":"数据卡不在本次授权范围"},ensure_ascii=False)
+        return json.dumps(cards[index],ensure_ascii=False)
+
+    @tool
+    def read_checks_and_rules() -> str:
+        """Read deterministic Skill outputs, human rules and rule findings for this run."""
+        return json.dumps({"values":snapshot.get("scalar_values",{}),"human_rules":snapshot.get("human_rules",[]),"findings":snapshot.get("rule_findings",[]),"evidence":sources},ensure_ascii=False)
+
+    @tool
+    def read_selected_skill(skill_id: str) -> str:
+        """Read only a native SKILL.md explicitly selected in the published plan."""
+        return skills.get(skill_id,"此 Skill 未被所选方案授权")
+
+    return [list_data_cards, read_data_card, read_checks_and_rules, read_selected_skill]