bex/gbnf.py

@@ -224,3 +224,98 @@ def grammar_noise_ratio(node, noise_tokens=None):
         return grammar_noise_ratio(node.child, noise_tokens)
 
     return 0, 0
+
+
+def grammar_quality_score(node):
+    """Score grammar quality (0.0 = useless, 1.0 = excellent).
+
+    Criteria:
+    - Has ordering (not a pure bag): +0.3
+    - Has multiple alternation groups: +0.2 per group (max 0.4)
+    - Has enough symbols (>=3 domain tokens): +0.2
+    - Not too short (>=2 concat parts): +0.1
+    """
+    from .grammar import Concat, Alt, Optional, Plus, Star
+
+    if node is None or isinstance(node, (Epsilon, Empty)):
+        return 0.0
+
+    score = 0.0
+
+    # Check for ordering (Concat with multiple parts)
+    if isinstance(node, Concat) and len(node.parts) >= 2:
+        score += 0.3
+
+    # Check for alternation groups
+    n_groups = _count_alt_groups(node)
+    score += min(0.4, n_groups * 0.2)
+
+    # Check symbol count
+    n_symbols = _count_symbols(node)
+    if n_symbols >= 3:
+        score += 0.2
+
+    # Check concat depth
+    n_concat = _count_concat_parts(node)
+    if n_concat >= 2:
+        score += 0.1
+
+    return min(1.0, score)
+
+
+def _count_alt_groups(node):
+    """Count alternation groups in AST."""
+    from .grammar import Concat, Alt, Optional, Plus, Star
+
+    if node is None or isinstance(node, (Epsilon, Empty, Symbol)):
+        return 0
+    if isinstance(node, Alt):
+        return 1 + sum(_count_alt_groups(p) for p in node.parts)
+    if isinstance(node, Concat):
+        return sum(_count_alt_groups(p) for p in node.parts)
+    if isinstance(node, (Plus, Optional, Star)):
+        return _count_alt_groups(node.child)
+    return 0
+
+
+def _count_symbols(node):
+    """Count total symbols in AST."""
+    from .grammar import Concat, Alt, Optional, Plus, Star
+
+    if node is None or isinstance(node, (Epsilon, Empty)):
+        return 0
+    if isinstance(node, Symbol):
+        return 1
+    if isinstance(node, Concat):
+        return sum(_count_symbols(p) for p in node.parts)
+    if isinstance(node, Alt):
+        return sum(_count_symbols(p) for p in node.parts)
+    if isinstance(node, (Plus, Optional, Star)):
+        return _count_symbols(node.child)
+    return 0
+
+
+def _count_concat_parts(node):
+    """Count top-level concat parts."""
+    from .grammar import Concat, Optional, Plus, Star
+
+    if isinstance(node, Concat):
+        return len(node.parts)
+    if isinstance(node, (Plus, Optional, Star)):
+        return _count_concat_parts(node.child)
+    return 1
+
+
+def is_useful_grammar(node, min_quality=0.3):
+    """Check if grammar is useful for LLM constraining.
+
+    A grammar is useful if:
+    1. Not empty after noise filtering
+    2. Has some structure (not a pure bag)
+    3. Has enough symbols to be constraining
+    """
+    if node is None or isinstance(node, (Epsilon, Empty)):
+        return False
+
+    quality = grammar_quality_score(node)
+    return quality >= min_quality

bex/tag_preprocessor/analyze.py

@@ -20,7 +20,7 @@ import pathspec
 
 from .code import preprocess_by_method, extract_arg_info, _summarize_arg_info
 from bex.ensemble import infer_ensemble
-from bex.gbnf import grammar_structure_score, to_gbnf, filter_noise, grammar_noise_ratio
+from bex.gbnf import grammar_structure_score, to_gbnf, filter_noise, grammar_noise_ratio, is_useful_grammar, grammar_quality_score
 from bex.grammar import Empty
 from bex.distributional import distributional_split
 from bex.decompose import decompose_with_coverage, get_decomposition_stats
@@ -878,7 +878,7 @@ def analyze_directory(
     return results
 
 
-def _build_json_output(results):
+def _build_json_output(results, min_quality=0.3):
     """Convert results dict to a compact JSON structure for prompt injection."""
     output = []
     for ext, clusters in results.items():
@@ -896,14 +896,19 @@ def _build_json_output(results):
                 filtered_grammar = filter_noise(grammar)
                 if filtered_grammar and not isinstance(filtered_grammar, Empty):
                     n_noise, n_total = grammar_noise_ratio(grammar)
+                    quality = grammar_quality_score(filtered_grammar)
                     entry["grammar"] = to_gbnf(filtered_grammar)
                     entry["grammar_clean"] = to_gbnf(filtered_grammar)
                     entry["noise_ratio"] = round(n_noise / n_total, 2) if n_total > 0 else 1.0
                     entry["symbols_before"] = n_total
                     entry["symbols_after"] = n_total - n_noise
+                    entry["quality"] = round(quality, 2)
+                    entry["useful"] = quality >= min_quality
                 else:
                     entry["grammar"] = to_gbnf(grammar)
                     entry["noise_ratio"] = 1.0
+                    entry["quality"] = 0.0
+                    entry["useful"] = False
                 entry["algorithm"] = result["best"]["algorithm"]
                 entry["mdl_score"] = round(result['best']['mdl_score'], 1)
             entry["imports"] = meta.get("imports", [])
@@ -914,11 +919,11 @@ def _build_json_output(results):
     return json.dumps(output, indent=2)
 
 
-def _build_yaml_output(results, dir_path, max_mdl=500.0, min_structure=0.0, filter_grammar_noise=True):
+def _build_yaml_output(results, dir_path, max_mdl=500.0, min_structure=0.0, filter_grammar_noise=True, min_quality=0.3):
     """Build YAML output grouped by top-level module, sorted by MDL.
 
     Filters out (other), no-grammar groups, groups above max_mdl,
-    and groups below min_structure.
+    groups below min_structure, and low-quality grammars.
     Returns YAML string.
     """
     import yaml
@@ -952,6 +957,10 @@ def _build_yaml_output(results, dir_path, max_mdl=500.0, min_structure=0.0, filt
                 else:
                     continue  # Skip grammars that become empty after filtering
 
+            # Apply quality gate
+            if not is_useful_grammar(grammar, min_quality):
+                continue
+
             # Extract top-level module from package path
             parts = label.replace(os.sep, "/").split("/")
             module = parts[0] if len(parts) > 1 else "(root)"
@@ -964,6 +973,7 @@ def _build_yaml_output(results, dir_path, max_mdl=500.0, min_structure=0.0, filt
                 "score": round(best.get("mdl_score", 0), 3),
                 "algorithm": best["algorithm"],
                 "mdl": round(best["mdl_score"], 1),
+                "quality": round(grammar_quality_score(grammar), 2),
             }
 
             modules.setdefault(module, []).append(entry)