update

tools/ai-review/agents/codebase_agent.py

@@ -96,7 +96,9 @@ class CodebaseAgent(BaseAgent):
 
     def execute(self, context: AgentContext) -> AgentResult:
         """Execute codebase analysis."""
-        self.logger.info(f"Starting codebase analysis for {context.owner}/{context.repo}")
+        self.logger.info(
+            f"Starting codebase analysis for {context.owner}/{context.repo}"
+        )
 
         actions_taken = []
 
@@ -192,7 +194,7 @@ class CodebaseAgent(BaseAgent):
 
                     # Check for docstrings (Python)
                     if ext == ".py":
-                        if 'def ' in content and '"""' not in content:
+                        if "def " in content and '"""' not in content:
                             metrics.missing_docstrings += 1
 
             except Exception as e:
@@ -273,23 +275,45 @@ Be constructive and actionable. Focus on the most impactful improvements.
             )
         except Exception as e:
             self.logger.error(f"AI analysis failed: {e}")
-            # Try to log the raw response if possible (requires accessing the last response)
-            # Since we don't have direct access here, we rely on having good logging in LLMClient if needed.
-            # But let's add a note to the summary.
+            self.logger.debug(f"Full error details: {type(e).__name__}: {str(e)}")
+
             # Calculate basic health score from metrics
             health_score = 70
             if metrics.todo_count > 10:
                 health_score -= 10
             if metrics.fixme_count > 5:
                 health_score -= 10
+            if metrics.deprecated_count > 3:
+                health_score -= 5
+
+            # Build recommendations based on metrics
+            recommendations = []
+            if metrics.todo_count > 5:
+                recommendations.append(
+                    f"Review and address {metrics.todo_count} TODO comments"
+                )
+            if metrics.fixme_count > 0:
+                recommendations.append(
+                    f"Review and fix {metrics.fixme_count} FIXME markers"
+                )
+            if metrics.deprecated_count > 0:
+                recommendations.append(
+                    f"Update {metrics.deprecated_count} deprecated code sections"
+                )
+            if metrics.missing_docstrings > 5:
+                recommendations.append("Consider adding more documentation")
+            if not recommendations:
+                recommendations.append("Codebase appears well-maintained")
 
             return CodebaseReport(
-                summary=f"Basic analysis complete (AI unavailable: {e})",
+                summary=f"Basic metrics analysis complete. {metrics.total_files} files analyzed across {len(metrics.languages)} languages.",
                 health_score=health_score,
                 metrics=metrics,
                 issues=[],
-                recommendations=["Manual review recommended"],
-                architecture_notes=[],
+                recommendations=recommendations,
+                architecture_notes=[
+                    f"Primary languages: {', '.join(list(metrics.languages.keys())[:3])}"
+                ],
             )
 
     def _get_key_files_content(
@@ -386,7 +410,11 @@ Be constructive and actionable. Focus on the most impactful improvements.
 
     def _generate_report_body(self, report: CodebaseReport) -> str:
         """Generate the report issue body."""
-        health_emoji = "🟢" if report.health_score >= 80 else ("🟡" if report.health_score >= 60 else "🔴")
+        health_emoji = (
+            "🟢"
+            if report.health_score >= 80
+            else ("🟡" if report.health_score >= 60 else "🔴")
+        )
 
         lines = [
             f"{self.AI_DISCLAIMER}",
@@ -427,7 +455,11 @@ Be constructive and actionable. Focus on the most impactful improvements.
             lines.append("")
             for issue in report.issues[:10]:
                 severity = issue.get("severity", "MEDIUM")
-                emoji = "🔴" if severity == "HIGH" else ("🟡" if severity == "MEDIUM" else "🟢")
+                emoji = (
+                    "🔴"
+                    if severity == "HIGH"
+                    else ("🟡" if severity == "MEDIUM" else "🟢")
+                )
                 lines.append(f"### [{severity}] {issue.get('category', 'General')}")
                 lines.append("")
                 lines.append(issue.get("description", ""))

tools/ai-review/agents/issue_agent.py

@@ -262,9 +262,7 @@ class IssueAgent(BaseAgent):
         if labels_to_add:
             try:
                 self.gitea.add_issue_labels(owner, repo, issue_index, labels_to_add)
-                return [
-                    name for name, id in label_map.items() if id in labels_to_add
-                ]
+                return [name for name, id in label_map.items() if id in labels_to_add]
             except Exception as e:
                 self.logger.warning(f"Failed to add labels: {e}")
 
@@ -336,6 +334,8 @@ class IssueAgent(BaseAgent):
             return self._command_explain(title, body)
         elif command == "suggest":
             return self._command_suggest(title, body)
+        elif command == "triage":
+            return self._command_triage(context, issue)
 
         return f"{self.AI_DISCLAIMER}\n\nSorry, I don't understand the command `{command}`."
 
@@ -390,3 +390,33 @@ Be practical and concise."""
             return f"{self.AI_DISCLAIMER}\n\n**Suggestions:**\n{response.content}"
         except Exception as e:
             return f"{self.AI_DISCLAIMER}\n\nSorry, I was unable to generate suggestions. Error: {e}"
+
+    def _command_triage(self, context: AgentContext, issue: dict) -> str:
+        """Perform full triage analysis on the issue."""
+        title = issue.get("title", "")
+        body = issue.get("body", "")
+        author = issue.get("user", {}).get("login", "unknown")
+        existing_labels = [l.get("name", "") for l in issue.get("labels", [])]
+        issue_index = issue.get("number")
+
+        try:
+            # Perform triage analysis
+            triage = self._triage_issue(title, body, author, existing_labels)
+
+            # Apply labels if enabled
+            agent_config = self.config.get("agents", {}).get("issue", {})
+            labels_applied = []
+            if agent_config.get("auto_label", True):
+                labels_applied = self._apply_labels(
+                    context.owner, context.repo, issue_index, triage
+                )
+
+            # Generate response
+            response = self._generate_triage_comment(triage, issue)
+
+            if labels_applied:
+                response += f"\n\n**Labels Applied:** {', '.join(labels_applied)}"
+
+            return response
+        except Exception as e:
+            return f"{self.AI_DISCLAIMER}\n\nSorry, I was unable to triage this issue. Error: {e}"