diff --git a/atlas-eval/src/main/scala/com/netflix/atlas/eval/stream/StreamContext.scala b/atlas-eval/src/main/scala/com/netflix/atlas/eval/stream/StreamContext.scala
index e3add16a3..aea49c0cf 100644
--- a/atlas-eval/src/main/scala/com/netflix/atlas/eval/stream/StreamContext.scala
+++ b/atlas-eval/src/main/scala/com/netflix/atlas/eval/stream/StreamContext.scala
@@ -30,7 +30,9 @@ import org.apache.pekko.stream.scaladsl.StreamConverters
 import org.apache.pekko.util.ByteString
 import com.netflix.atlas.core.model.DataExpr
 import com.netflix.atlas.core.model.Query
+import com.netflix.atlas.core.model.StyleExpr
 import com.netflix.atlas.core.util.Streams
+import com.netflix.atlas.eval.model.ExprType
 import com.netflix.atlas.eval.stream.Evaluator.DataSource
 import com.netflix.atlas.eval.stream.Evaluator.DataSources
 import com.netflix.atlas.json.JsonSupport
@@ -163,14 +165,11 @@ private[stream] class StreamContext(
 
       // Check that expression is parseable and perform basic static analysis of DataExprs to
       // weed out expensive queries up front
-      val results = interpreter.eval(uri).exprs
-      results.foreach(_.expr.dataExprs.foreach(validateDataExpr))
-
-      // For hi-res streams, require more precise scoping that allows us to more efficiently
-      // match the data and run it only where needed. This would ideally be applied everywhere,
-      // but for backwards compatiblity the 1m step is opted out for now.
-      if (ds.step.toMillis < 60_000) {
-        results.foreach(_.expr.dataExprs.foreach(expr => restrictsNameAndApp(expr.query)))
+      val (exprType, exprs) = interpreter.parseQuery(uri)
+      if (exprType == ExprType.TIME_SERIES) {
+        exprs.foreach {
+          case e: StyleExpr => validateStyleExpr(e, ds)
+        }
       }
 
       // Check that there is a backend available for it
@@ -181,6 +180,17 @@ private[stream] class StreamContext(
     }
   }
 
+  private def validateStyleExpr(styleExpr: StyleExpr, ds: DataSource): Unit = {
+    styleExpr.expr.dataExprs.foreach(validateDataExpr)
+
+    // For hi-res streams, require more precise scoping that allows us to more efficiently
+    // match the data and run it only where needed. This would ideally be applied everywhere,
+    // but for backwards compatiblity the 1m step is opted out for now.
+    if (ds.step.toMillis < 60_000) {
+      styleExpr.expr.dataExprs.foreach(expr => restrictsNameAndApp(expr.query))
+    }
+  }
+
   private def validateDataExpr(expr: DataExpr): Unit = {
     Query
       .dnfList(expr.query)
diff --git a/atlas-eval/src/test/scala/com/netflix/atlas/eval/stream/EvaluatorSuite.scala b/atlas-eval/src/test/scala/com/netflix/atlas/eval/stream/EvaluatorSuite.scala
index e4364c3f2..5dc45cd0e 100644
--- a/atlas-eval/src/test/scala/com/netflix/atlas/eval/stream/EvaluatorSuite.scala
+++ b/atlas-eval/src/test/scala/com/netflix/atlas/eval/stream/EvaluatorSuite.scala
@@ -463,11 +463,11 @@ class EvaluatorSuite extends FunSuite {
     assertEquals(ds.step, Duration.ofMinutes(1))
   }
 
-  private def validateOk(params: String): Unit = {
+  private def validateOk(params: String, path: String = "graph"): Unit = {
     val evaluator = new Evaluator(config, registry, system)
     val ds = new Evaluator.DataSource(
       "test",
-      s"resource:///gc-pause.dat?$params"
+      s"synthetic://test/$path?$params"
     )
     evaluator.validate(ds)
   }
@@ -585,6 +585,25 @@ class EvaluatorSuite extends FunSuite {
     )
   }
 
+  test("validate: events raw") {
+    validateOk("q=name,foo,:eq,nf.cluster,www-dev,:eq,:and", path = "events")
+  }
+
+  test("validate: events table") {
+    validateOk("q=name,foo,:eq,nf.cluster,www-dev,:eq,:and,(,value,),:table", path = "events")
+  }
+
+  test("validate: traces") {
+    validateOk("q=nf.app,www,:eq,nf.app,db,:eq,:child", path = "traces")
+  }
+
+  test("validate: trace time series") {
+    validateOk(
+      "q=app,www,:eq,app,db,:eq,:child,app,db,:eq,:sum,:span-time-series",
+      path = "traces/graph"
+    )
+  }
+
   private def invalidHiResQuery(expr: String): Unit = {
     val evaluator = new Evaluator(config, registry, system)
     val ds = new Evaluator.DataSource(