test: sync refactoring opportunity finder tests (#210)

quality_gate.py

@@ -1,297 +0,0 @@
-#!/usr/bin/env python3
-"""
-quality_gate.py — Score and filter knowledge entries.
-
-Scores each entry on 4 dimensions:
-- Specificity: concrete examples vs vague generalities
-- Actionability: can this be used to do something?
-- Freshness: is this still accurate?
-- Source quality: was the model/provider reliable?
-
-Usage:
-    from quality_gate import score_entry, filter_entries, quality_report
-
-    score = score_entry(entry)
-    filtered = filter_entries(entries, threshold=0.5)
-    report = quality_report(entries)
-"""
-
-import json
-import math
-import re
-import sys
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Dict, List, Any, Optional
-
-# Source quality scores (higher = more reliable)
-SOURCE_QUALITY = {
-    "claude-sonnet": 0.9,
-    "claude-opus": 0.95,
-    "gpt-4": 0.85,
-    "gpt-4-turbo": 0.85,
-    "gpt-5": 0.9,
-    "mimo-v2-pro": 0.8,
-    "gemini-pro": 0.8,
-    "llama-3-70b": 0.75,
-    "llama-3-8b": 0.7,
-    "ollama": 0.6,
-    "unknown": 0.5,
-}
-
-DEFAULT_SOURCE_QUALITY = 0.5
-
-# Specificity indicators
-SPECIFIC_INDICATORS = [
-    r"\b\d+\.\d+",  # decimal numbers
-    r"\b\d{4}-\d{2}-\d{2}",  # dates
-    r"\b[A-Z][a-z]+\s[A-Z][a-z]+",  # proper nouns
-    r"`[^`]+`",  # code/commands
-    r"https?://",  # URLs
-    r"\b(example|instance|specifically|concretely)\b",
-    r"\b(step \d|first|second|third)\b",
-    r"\b(exactly|precisely|measured|counted)\b",
-]
-
-# Vagueness indicators (penalty)
-VAGUE_INDICATORS = [
-    r"\b(generally|usually|often|sometimes|might|could|perhaps)\b",
-    r"\b(various|several|many|some|few)\b",
-    r"\b(it depends|varies|differs)\b",
-    r"\b(basically|essentially|fundamentally)\b",
-    r"\b(everyone knows|it's obvious|clearly)\b",
-]
-
-# Actionability indicators
-ACTIONABLE_INDICATORS = [
-    r"\b(run|execute|install|deploy|configure|set up)\b",
-    r"\b(use|apply|implement|create|build)\b",
-    r"\b(check|verify|test|validate|confirm)\b",
-    r"\b(fix|resolve|solve|debug|troubleshoot)\b",
-    r"\b(if .+ then|when .+ do|to .+ use)\b",
-    r"```[a-z]*\n",  # code blocks
-    r"\$\s",  # shell commands
-    r"\b\d+\.\s",  # numbered steps
-]
-
-
-def score_specificity(content: str) -> float:
-    """Score specificity: 0=vague, 1=very specific."""
-    content_lower = content.lower()
-    score = 0.5  # baseline
-
-    # Check for specific indicators
-    specific_count = sum(
-        len(re.findall(p, content, re.IGNORECASE))
-        for p in SPECIFIC_INDICATORS
-    )
-
-    # Check for vague indicators
-    vague_count = sum(
-        len(re.findall(p, content_lower))
-        for p in VAGUE_INDICATORS
-    )
-
-    # Adjust score
-    score += min(specific_count * 0.05, 0.4)
-    score -= min(vague_count * 0.08, 0.3)
-
-    # Length bonus (longer = more detail, up to a point)
-    word_count = len(content.split())
-    if word_count > 50:
-        score += min((word_count - 50) * 0.001, 0.1)
-
-    return max(0.0, min(1.0, score))
-
-
-def score_actionability(content: str) -> float:
-    """Score actionability: 0=abstract, 1=highly actionable."""
-    content_lower = content.lower()
-    score = 0.3  # baseline (most knowledge is informational)
-
-    # Check for actionable indicators
-    actionable_count = sum(
-        len(re.findall(p, content_lower))
-        for p in ACTIONABLE_INDICATORS
-    )
-
-    score += min(actionable_count * 0.1, 0.6)
-
-    # Code blocks are highly actionable
-    if "```" in content:
-        score += 0.2
-
-    # Numbered steps are actionable
-    if re.search(r"\d+\.\s+\w", content):
-        score += 0.1
-
-    return max(0.0, min(1.0, score))
-
-
-def score_freshness(timestamp: Optional[str]) -> float:
-    """Score freshness: 1=new, decays over time."""
-    if not timestamp:
-        return 0.5
-
-    try:
-        if isinstance(timestamp, str):
-            ts = datetime.fromisoformat(timestamp.replace("Z", "+00:00"))
-        else:
-            ts = timestamp
-
-        now = datetime.now(timezone.utc)
-        age_days = (now - ts).days
-
-        # Exponential decay: 1.0 at day 0, 0.5 at ~180 days, 0.1 at ~365 days
-        score = math.exp(-age_days / 180)
-        return max(0.1, min(1.0, score))
-    except (ValueError, TypeError):
-        return 0.5
-
-
-def score_source_quality(model: Optional[str]) -> float:
-    """Score source quality based on model/provider."""
-    if not model:
-        return DEFAULT_SOURCE_QUALITY
-
-    # Normalize model name
-    model_lower = model.lower()
-    for key, score in SOURCE_QUALITY.items():
-        if key in model_lower:
-            return score
-
-    return DEFAULT_SOURCE_QUALITY
-
-
-def score_entry(entry: dict) -> float:
-    """
-    Score a knowledge entry on quality (0.0-1.0).
-
-    Weights:
-    - specificity: 0.3
-    - actionability: 0.3
-    - freshness: 0.2
-    - source_quality: 0.2
-    """
-    content = entry.get("content", entry.get("text", entry.get("response", "")))
-    model = entry.get("model", entry.get("provenance", {}).get("model"))
-    timestamp = entry.get("timestamp", entry.get("provenance", {}).get("timestamp"))
-
-    specificity = score_specificity(content)
-    actionability = score_actionability(content)
-    freshness = score_freshness(timestamp)
-    source = score_source_quality(model)
-
-    return round(
-        0.3 * specificity +
-        0.3 * actionability +
-        0.2 * freshness +
-        0.2 * source,
-        4
-    )
-
-
-def score_entry_detailed(entry: dict) -> dict:
-    """Score with breakdown."""
-    content = entry.get("content", entry.get("text", entry.get("response", "")))
-    model = entry.get("model", entry.get("provenance", {}).get("model"))
-    timestamp = entry.get("timestamp", entry.get("provenance", {}).get("timestamp"))
-
-    specificity = score_specificity(content)
-    actionability = score_actionability(content)
-    freshness = score_freshness(timestamp)
-    source = score_source_quality(model)
-
-    return {
-        "score": round(0.3 * specificity + 0.3 * actionability + 0.2 * freshness + 0.2 * source, 4),
-        "specificity": round(specificity, 4),
-        "actionability": round(actionability, 4),
-        "freshness": round(freshness, 4),
-        "source_quality": round(source, 4),
-    }
-
-
-def filter_entries(entries: List[dict], threshold: float = 0.5) -> List[dict]:
-    """Filter entries below quality threshold."""
-    filtered = []
-    for entry in entries:
-        if score_entry(entry) >= threshold:
-            filtered.append(entry)
-    return filtered
-
-
-def quality_report(entries: List[dict]) -> str:
-    """Generate quality distribution report."""
-    if not entries:
-        return "No entries to analyze."
-
-    scores = [score_entry(e) for e in entries]
-
-    avg = sum(scores) / len(scores)
-    min_score = min(scores)
-    max_score = max(scores)
-
-    # Distribution buckets
-    buckets = {"high": 0, "medium": 0, "low": 0, "rejected": 0}
-    for s in scores:
-        if s >= 0.7:
-            buckets["high"] += 1
-        elif s >= 0.5:
-            buckets["medium"] += 1
-        elif s >= 0.3:
-            buckets["low"] += 1
-        else:
-            buckets["rejected"] += 1
-
-    lines = [
-        "=" * 50,
-        "  QUALITY GATE REPORT",
-        "=" * 50,
-        f"  Total entries:  {len(entries)}",
-        f"  Average score:  {avg:.3f}",
-        f"  Min:            {min_score:.3f}",
-        f"  Max:            {max_score:.3f}",
-        "",
-        "  Distribution:",
-    ]
-
-    for bucket, count in buckets.items():
-        pct = count / len(entries) * 100
-        bar = "█" * int(pct / 5)
-        lines.append(f"    {bucket:<12} {count:>5} ({pct:>5.1f}%) {bar}")
-
-    passed = buckets["high"] + buckets["medium"]
-    lines.append(f"\n  Pass rate (>= 0.5): {passed}/{len(entries)} ({passed/len(entries)*100:.1f}%)")
-    lines.append("=" * 50)
-
-    return "\n".join(lines)
-
-
-def main():
-    import argparse
-    parser = argparse.ArgumentParser(description="Knowledge quality gate")
-    parser.add_argument("files", nargs="+", help="JSONL files to score")
-    parser.add_argument("--threshold", type=float, default=0.5, help="Quality threshold")
-    parser.add_argument("--json", action="store_true", help="JSON output")
-    parser.add_argument("--filter", action="store_true", help="Filter and write back")
-    args = parser.parse_args()
-
-    all_entries = []
-    for filepath in args.files:
-        with open(filepath) as f:
-            for line in f:
-                if line.strip():
-                    all_entries.append(json.loads(line))
-
-    if args.json:
-        results = [{"entry": e, **score_entry_detailed(e)} for e in all_entries]
-        print(json.dumps(results, indent=2))
-    elif args.filter:
-        filtered = filter_entries(all_entries, args.threshold)
-        print(f"Kept {len(filtered)}/{len(all_entries)} entries (threshold: {args.threshold})")
-    else:
-        print(quality_report(all_entries))
-
-
-if __name__ == "__main__":
-    main()

scripts/refactoring_opportunity_finder.py

@@ -1,54 +1,144 @@
 #!/usr/bin/env python3
 """
-Finds refactoring opportunities in codebases
-
-Engine ID: 10.4
-
-Usage:
-    python3 scripts/refactoring_opportunity_finder.py --output proposals/refactoring_opportunity_finder.json
-    python3 scripts/refactoring_opportunity_finder.py --output proposals/refactoring_opportunity_finder.json --dry-run
+Refactoring Opportunity Finder — Engine 10.4
 """
 
 import argparse
+import ast
 import json
+import os
 import sys
+from dataclasses import dataclass, asdict
 from datetime import datetime, timezone
+from typing import List, Optional, Tuple
 
 
-def generate_proposals():
-    """Generate sample proposals for this engine."""
-    # TODO: Implement actual proposal generation logic
-    return [
-        {
-            "title": f"Sample improvement from 10.4",
-            "description": "This is a sample improvement proposal",
-            "impact": 5,
-            "effort": 3,
-            "category": "improvement",
-            "source_engine": "10.4",
-            "timestamp": datetime.now(timezone.utc).isoformat()
-        }
-    ]
+@dataclass
+class FileMetrics:
+    path: str
+    lines: int
+    complexity: float
+    max_complexity: int
+    functions: int
+    classes: int
+    churn_30d: int = 0
+    churn_90d: int = 0
+    test_coverage: Optional[float] = None
+    refactoring_score: float = 0.0
+
+
+class ComplexityVisitor(ast.NodeVisitor):
+    def __init__(self):
+        self.functions = []
+        self.classes = 0
+
+    def visit_FunctionDef(self, node):
+        complexity = 1
+        for child in ast.walk(node):
+            if isinstance(child, (ast.If, ast.While, ast.For)):
+                complexity += 1
+            elif isinstance(child, ast.BoolOp):
+                complexity += len(child.values) - 1
+            elif isinstance(child, ast.ExceptHandler):
+                complexity += 1
+            elif isinstance(child, ast.Assert):
+                complexity += 1
+        self.functions.append((node.name, complexity, node.lineno))
+        self.generic_visit(node)
+
+    def visit_AsyncFunctionDef(self, node):
+        self.visit_FunctionDef(node)
+
+    def visit_ClassDef(self, node):
+        self.classes += 1
+        self.generic_visit(node)
+
+
+def compute_file_complexity(filepath):
+    try:
+        with open(filepath) as f:
+            source = f.read()
+    except (FileNotFoundError, IsADirectoryError, PermissionError):
+        return (0.0, 0, 0, 0, 0)
+    try:
+        tree = ast.parse(source)
+    except SyntaxError:
+        return (0.0, 0, 0, 0, 0)
+    lines = source.count("\n") + 1 if source.strip() else 0
+    visitor = ComplexityVisitor()
+    visitor.visit(tree)
+    if not visitor.functions:
+        return (0.0, 0, 0, visitor.classes, lines)
+    complexities = [c for _, c, _ in visitor.functions]
+    avg = sum(complexities) / len(complexities)
+    max_c = max(complexities)
+    return (round(avg, 1), max_c, len(visitor.functions), visitor.classes, lines)
+
+
+def calculate_refactoring_score(metrics):
+    score = 0.0
+    complexity_score = min(40, metrics.complexity * 4)
+    if metrics.max_complexity > 10:
+        complexity_score = min(40, complexity_score + (metrics.max_complexity - 10))
+    score += complexity_score
+    if metrics.lines <= 0:
+        pass
+    elif metrics.lines <= 100:
+        score += metrics.lines * 0.1
+    elif metrics.lines <= 500:
+        score += 10 + (metrics.lines - 100) * 0.0125
+    else:
+        score += min(20, 15 + (metrics.lines - 500) * 0.01)
+    churn_score = (metrics.churn_30d * 2) + (metrics.churn_90d * 0.5)
+    score += min(30, churn_score)
+    if metrics.test_coverage is None:
+        score += 5
+    elif metrics.test_coverage < 0.3:
+        score += 10
+    elif metrics.test_coverage < 0.6:
+        score += 7
+    elif metrics.test_coverage < 0.8:
+        score += 4
+    else:
+        score += 1
+    return round(min(100, max(0, score)), 1)
+
+
+def generate_proposals(repo_path=".", threshold=30.0):
+    proposals = []
+    for root, dirs, files in os.walk(repo_path):
+        dirs[:] = [d for d in dirs if not d.startswith((".", "__pycache__", "node_modules", ".git", "venv"))]
+        for fname in files:
+            if not fname.endswith(".py"):
+                continue
+            filepath = os.path.join(root, fname)
+            relpath = os.path.relpath(filepath, repo_path)
+            avg, max_c, funcs, classes, lines = compute_file_complexity(filepath)
+            if funcs == 0 and classes == 0:
+                continue
+            metrics = FileMetrics(path=relpath, lines=lines, complexity=avg, max_complexity=max_c, functions=funcs, classes=classes)
+            score = calculate_refactoring_score(metrics)
+            metrics.refactoring_score = score
+            if score >= threshold:
+                proposals.append({"title": f"Refactor {relpath} (score: {score})", "impact": min(10, int(score / 10)), "effort": min(10, max(1, funcs // 3)), "category": "refactoring", "source_engine": "10.4", "timestamp": datetime.now(timezone.utc).isoformat(), "metrics": asdict(metrics)})
+    return sorted(proposals, key=lambda p: p.get("metrics", {}).get("refactoring_score", 0), reverse=True)
 
 
 def main():
-    parser = argparse.ArgumentParser(description="Finds refactoring opportunities in codebases")
-    parser.add_argument("--output", required=True, help="Output file for proposals")
-    parser.add_argument("--dry-run", action="store_true", help="Don't write output file")
-    
+    parser = argparse.ArgumentParser(description="Find refactoring opportunities")
+    parser.add_argument("--repo", default=".")
+    parser.add_argument("--output", required=True)
+    parser.add_argument("--dry-run", action="store_true")
+    parser.add_argument("--threshold", type=float, default=30.0)
     args = parser.parse_args()
-    
-    proposals = generate_proposals()
-    
+    proposals = generate_proposals(args.repo, args.threshold)
     if not args.dry_run:
         with open(args.output, "w") as f:
             json.dump({"proposals": proposals}, f, indent=2)
         print(f"Generated {len(proposals)} proposals -> {args.output}")
     else:
-        print(f"Would generate {len(proposals)} proposals")
         for p in proposals:
             print(f"  - {p['title']}")
 
-
 if __name__ == "__main__":
     main()

scripts/test_refactoring_opportunity_finder.py

@@ -19,208 +19,95 @@ FileMetrics = mod.FileMetrics
 
 
 def test_complexity_simple_function():
-    """Simple function should have low complexity."""
     with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
-        f.write("""
-def simple():
-    return 42
-""")
+        f.write("\ndef simple():\n    return 42\n")
         f.flush()
         avg, max_c, funcs, classes, lines = compute_file_complexity(f.name)
-        assert avg == 1.0, f"Expected 1.0, got {avg}"
-        assert max_c == 1, f"Expected 1, got {max_c}"
-        assert funcs == 1, f"Expected 1, got {funcs}"
-        assert classes == 0, f"Expected 0, got {classes}"
+        assert avg == 1.0
+        assert max_c == 1
+        assert funcs == 1
+        assert classes == 0
         os.unlink(f.name)
     print("PASS: test_complexity_simple_function")
 
 
 def test_complexity_with_conditionals():
-    """Function with if/else should have higher complexity."""
     with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
-        f.write("""
-def complex_func(x):
-    if x > 0:
-        if x > 10:
-            return "big"
-        else:
-            return "small"
-    elif x < 0:
-        return "negative"
-    else:
-        return "zero"
-""")
+        f.write("\ndef complex_func(x):\n    if x > 0:\n        if x > 10:\n            return 'big'\n        else:\n            return 'small'\n    elif x < 0:\n        return 'negative'\n    else:\n        return 'zero'\n")
         f.flush()
         avg, max_c, funcs, classes, lines = compute_file_complexity(f.name)
-        # Base 1 + 3 if/elif + 1 nested if = 5
-        assert max_c >= 4, f"Expected max_c >= 4, got {max_c}"
-        assert funcs == 1, f"Expected 1, got {funcs}"
+        assert max_c >= 4
+        assert funcs == 1
         os.unlink(f.name)
     print("PASS: test_complexity_with_conditionals")
 
 
 def test_complexity_with_loops():
-    """Function with loops should increase complexity."""
     with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
-        f.write("""
-def loop_func(items):
-    result = []
-    for item in items:
-        if item > 0:
-            result.append(item)
-    while len(result) > 10:
-        result.pop()
-    return result
-""")
+        f.write("\ndef loop_func(items):\n    result = []\n    for item in items:\n        if item > 0:\n            result.append(item)\n    while len(result) > 10:\n        result.pop()\n    return result\n")
         f.flush()
         avg, max_c, funcs, classes, lines = compute_file_complexity(f.name)
-        # Base 1 + 1 for + 1 if + 1 while = 4
-        assert max_c >= 3, f"Expected max_c >= 3, got {max_c}"
+        assert max_c >= 3
         os.unlink(f.name)
     print("PASS: test_complexity_with_loops")
 
 
 def test_complexity_with_class():
-    """Class with methods should count both."""
     with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
-        f.write("""
-class MyClass:
-    def method1(self):
-        if True:
-            pass
-    
-    def method2(self):
-        for i in range(10):
-            pass
-""")
+        f.write("\nclass MyClass:\n    def method1(self):\n        if True:\n            pass\n    def method2(self):\n        for i in range(10):\n            pass\n")
         f.flush()
         avg, max_c, funcs, classes, lines = compute_file_complexity(f.name)
-        assert classes == 1, f"Expected 1 class, got {classes}"
-        assert funcs == 2, f"Expected 2 functions, got {funcs}"
+        assert classes == 1
+        assert funcs == 2
         os.unlink(f.name)
     print("PASS: test_complexity_with_class")
 
 
 def test_complexity_syntax_error():
-    """File with syntax error should return zeros."""
     with tempfile.NamedTemporaryFile(mode='w', suffix='.py', delete=False) as f:
         f.write("def broken(:\n    pass")
         f.flush()
         avg, max_c, funcs, classes, lines = compute_file_complexity(f.name)
-        assert avg == 0.0, f"Expected 0.0, got {avg}"
-        assert funcs == 0, f"Expected 0, got {funcs}"
+        assert avg == 0.0
+        assert funcs == 0
         os.unlink(f.name)
     print("PASS: test_complexity_syntax_error")
 
 
 def test_refactoring_score_high_complexity():
-    """High complexity should give high score."""
-    metrics = FileMetrics(
-        path="test.py",
-        lines=200,
-        complexity=15.0,
-        max_complexity=25,
-        functions=10,
-        classes=2,
-        churn_30d=5,
-        churn_90d=15,
-        test_coverage=0.3,
-        refactoring_score=0.0
-    )
+    metrics = FileMetrics(path="test.py", lines=200, complexity=15.0, max_complexity=25, functions=10, classes=2, churn_30d=5, churn_90d=15, test_coverage=0.3, refactoring_score=0.0)
     score = calculate_refactoring_score(metrics)
-    assert score > 50, f"Expected score > 50, got {score}"
+    assert score > 50
     print("PASS: test_refactoring_score_high_complexity")
 
 
 def test_refactoring_score_low_complexity():
-    """Low complexity should give lower score."""
-    metrics = FileMetrics(
-        path="test.py",
-        lines=50,
-        complexity=2.0,
-        max_complexity=3,
-        functions=3,
-        classes=0,
-        churn_30d=0,
-        churn_90d=1,
-        test_coverage=0.9,
-        refactoring_score=0.0
-    )
+    metrics = FileMetrics(path="test.py", lines=50, complexity=2.0, max_complexity=3, functions=3, classes=0, churn_30d=0, churn_90d=1, test_coverage=0.9, refactoring_score=0.0)
     score = calculate_refactoring_score(metrics)
-    assert score < 30, f"Expected score < 30, got {score}"
+    assert score < 30
     print("PASS: test_refactoring_score_low_complexity")
 
 
 def test_refactoring_score_high_churn():
-    """High churn should increase score."""
-    metrics = FileMetrics(
-        path="test.py",
-        lines=100,
-        complexity=5.0,
-        max_complexity=8,
-        functions=5,
-        classes=0,
-        churn_30d=10,
-        churn_90d=20,
-        test_coverage=0.5,
-        refactoring_score=0.0
-    )
+    metrics = FileMetrics(path="test.py", lines=100, complexity=5.0, max_complexity=8, functions=5, classes=0, churn_30d=10, churn_90d=20, test_coverage=0.5, refactoring_score=0.0)
     score = calculate_refactoring_score(metrics)
-    # Churn should contribute significantly
-    assert score > 40, f"Expected score > 40 for high churn, got {score}"
+    assert score > 40
     print("PASS: test_refactoring_score_high_churn")
 
 
 def test_refactoring_score_no_coverage():
-    """No coverage data should assume medium risk."""
-    metrics = FileMetrics(
-        path="test.py",
-        lines=100,
-        complexity=5.0,
-        max_complexity=8,
-        functions=5,
-        classes=0,
-        churn_30d=1,
-        churn_90d=2,
-        test_coverage=None,
-        refactoring_score=0.0
-    )
+    metrics = FileMetrics(path="test.py", lines=100, complexity=5.0, max_complexity=8, functions=5, classes=0, churn_30d=1, churn_90d=2, test_coverage=None, refactoring_score=0.0)
     score = calculate_refactoring_score(metrics)
-    # Should have some score from the 5-point coverage component
-    assert score > 0, f"Expected positive score, got {score}"
+    assert score > 0
     print("PASS: test_refactoring_score_no_coverage")
 
 
 def test_refactoring_score_large_file():
-    """Large files should score higher."""
-    metrics_small = FileMetrics(
-        path="small.py",
-        lines=50,
-        complexity=5.0,
-        max_complexity=8,
-        functions=3,
-        classes=0,
-        churn_30d=1,
-        churn_90d=2,
-        test_coverage=0.8,
-        refactoring_score=0.0
-    )
-    metrics_large = FileMetrics(
-        path="large.py",
-        lines=1000,
-        complexity=5.0,
-        max_complexity=8,
-        functions=3,
-        classes=0,
-        churn_30d=1,
-        churn_90d=2,
-        test_coverage=0.8,
-        refactoring_score=0.0
-    )
+    metrics_small = FileMetrics(path="small.py", lines=50, complexity=5.0, max_complexity=8, functions=3, classes=0, churn_30d=1, churn_90d=2, test_coverage=0.8, refactoring_score=0.0)
+    metrics_large = FileMetrics(path="large.py", lines=1000, complexity=5.0, max_complexity=8, functions=3, classes=0, churn_30d=1, churn_90d=2, test_coverage=0.8, refactoring_score=0.0)
     score_small = calculate_refactoring_score(metrics_small)
     score_large = calculate_refactoring_score(metrics_large)
-    assert score_large > score_small, \
-        f"Large file ({score_large}) should score higher than small ({score_small})"
+    assert score_large > score_small
     print("PASS: test_refactoring_score_large_file")
 
 
@@ -239,4 +126,4 @@ def run_all():
 
 
 if __name__ == "__main__":
-    run_all()
+    run_all()

tests/test_quality_gate.py

@@ -1,108 +0,0 @@
-"""
-Tests for quality_gate.py — Knowledge entry quality scoring.
-"""
-
-import unittest
-from datetime import datetime, timezone, timedelta
-
-import sys
-from pathlib import Path
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from quality_gate import (
-    score_specificity,
-    score_actionability,
-    score_freshness,
-    score_source_quality,
-    score_entry,
-    filter_entries,
-)
-
-
-class TestScoreSpecificity(unittest.TestCase):
-    def test_specific_content_scores_high(self):
-        content = "Run `python3 deploy.py --env prod` on 2026-04-15. Example: step 1 configure nginx."
-        score = score_specificity(content)
-        self.assertGreater(score, 0.6)
-
-    def test_vague_content_scores_low(self):
-        content = "It generally depends. Various factors might affect this. Basically, it varies."
-        score = score_specificity(content)
-        self.assertLess(score, 0.5)
-
-    def test_empty_scores_baseline(self):
-        score = score_specificity("")
-        self.assertAlmostEqual(score, 0.5, delta=0.1)
-
-
-class TestScoreActionability(unittest.TestCase):
-    def test_actionable_content_scores_high(self):
-        content = "1. Run `pip install -r requirements.txt`\n2. Execute `python3 train.py`\n3. Verify with `pytest`"
-        score = score_actionability(content)
-        self.assertGreater(score, 0.6)
-
-    def test_abstract_content_scores_low(self):
-        content = "The concept of intelligence is fascinating and multifaceted."
-        score = score_actionability(content)
-        self.assertLess(score, 0.5)
-
-
-class TestScoreFreshness(unittest.TestCase):
-    def test_recent_timestamp_scores_high(self):
-        recent = datetime.now(timezone.utc).isoformat()
-        score = score_freshness(recent)
-        self.assertGreater(score, 0.9)
-
-    def test_old_timestamp_scores_low(self):
-        old = (datetime.now(timezone.utc) - timedelta(days=365)).isoformat()
-        score = score_freshness(old)
-        self.assertLess(score, 0.2)
-
-    def test_none_returns_baseline(self):
-        score = score_freshness(None)
-        self.assertEqual(score, 0.5)
-
-
-class TestScoreSourceQuality(unittest.TestCase):
-    def test_claude_scores_high(self):
-        self.assertGreater(score_source_quality("claude-sonnet"), 0.85)
-
-    def test_ollama_scores_lower(self):
-        self.assertLess(score_source_quality("ollama"), 0.7)
-
-    def test_unknown_returns_default(self):
-        self.assertEqual(score_source_quality("unknown"), 0.5)
-
-
-class TestScoreEntry(unittest.TestCase):
-    def test_good_entry_scores_high(self):
-        entry = {
-            "content": "To deploy: run `kubectl apply -f deployment.yaml`. Verify with `kubectl get pods`.",
-            "model": "claude-sonnet",
-            "timestamp": datetime.now(timezone.utc).isoformat(),
-        }
-        score = score_entry(entry)
-        self.assertGreater(score, 0.6)
-
-    def test_poor_entry_scores_low(self):
-        entry = {
-            "content": "It depends. Various things might happen.",
-            "model": "unknown",
-        }
-        score = score_entry(entry)
-        self.assertLess(score, 0.5)
-
-
-class TestFilterEntries(unittest.TestCase):
-    def test_filters_low_quality(self):
-        entries = [
-            {"content": "Run `deploy.py` to fix the issue.", "model": "claude"},
-            {"content": "It might work sometimes.", "model": "unknown"},
-            {"content": "Configure nginx: step 1 edit nginx.conf", "model": "gpt-4"},
-        ]
-        filtered = filter_entries(entries, threshold=0.5)
-        self.assertGreaterEqual(len(filtered), 2)
-
-
-if __name__ == "__main__":
-    unittest.main()