firefrost-gaming/skill-seekers-reference
3
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

style: Format all Python files with ruff

Browse Source 
- Formatted 103 files to comply with ruff format requirements
- No code logic changes, only formatting/whitespace
- Fixes CI formatting check failures
This commit is contained in:
yusyus
2026-02-08 14:42:27 +03:00
parent 6e4f623b9d
commit 0265de5816
103 changed files with 2241 additions and 2627 deletions
Download Patch File Download Diff File Expand all files Collapse all files

145
src/skill_seekers/cli/quality_metrics.py
View File

@@ -16,6 +16,7 @@ from enum import Enum
class MetricLevel(Enum):
"""Metric severity level."""
INFO = "info"
WARNING = "warning"
ERROR = "error"
@@ -25,6 +26,7 @@ class MetricLevel(Enum):
@dataclass
class QualityMetric:
"""Individual quality metric."""
name: str
value: float # 0.0-1.0 (or 0-100 percentage)
level: MetricLevel
@@ -35,6 +37,7 @@ class QualityMetric:
@dataclass
class QualityScore:
"""Overall quality score."""
total_score: float # 0-100
completeness: float # 0-100
accuracy: float # 0-100
@@ -46,6 +49,7 @@ class QualityScore:
@dataclass
class QualityReport:
"""Complete quality report."""
timestamp: str
skill_name: str
overall_score: QualityScore
@@ -64,10 +68,17 @@ class QualityAnalyzer:
# Thresholds for quality grades
GRADE_THRESHOLDS = {
'A+': 95, 'A': 90, 'A-': 85,
'B+': 80, 'B': 75, 'B-': 70,
'C+': 65, 'C': 60, 'C-': 55,
'D': 50, 'F': 0
"A+": 95,
"A": 90,
"A-": 85,
"B+": 80,
"B": 75,
"B-": 70,
"C+": 65,
"C": 60,
"C-": 55,
"D": 50,
"F": 0,
}
def __init__(self, skill_dir: Path):
@@ -102,7 +113,7 @@ class QualityAnalyzer:
score += 10
# Has sections (10 points)
if content.count('#') >= 5:
if content.count("#") >= 5:
score += 10
# References directory (20 points)
@@ -134,13 +145,15 @@ class QualityAnalyzer:
if len(suggestions) == 0:
suggestions.append("Expand documentation coverage")
self.metrics.append(QualityMetric(
name="Completeness",
value=completeness,
level=level,
description=f"Documentation completeness: {completeness:.1f}%",
suggestions=suggestions
))
self.metrics.append(
QualityMetric(
name="Completeness",
value=completeness,
level=level,
description=f"Documentation completeness: {completeness:.1f}%",
suggestions=suggestions,
)
)
return completeness
@@ -166,14 +179,14 @@ class QualityAnalyzer:
content = skill_md.read_text(encoding="utf-8")
# Check for TODO markers (deduct 5 points each, max 20)
todo_count = content.lower().count('todo')
todo_count = content.lower().count("todo")
if todo_count > 0:
deduction = min(todo_count * 5, 20)
score -= deduction
issues.append(f"Found {todo_count} TODO markers")
# Check for placeholder text (deduct 10)
placeholders = ['lorem ipsum', 'placeholder', 'coming soon']
placeholders = ["lorem ipsum", "placeholder", "coming soon"]
for placeholder in placeholders:
if placeholder in content.lower():
score -= 10
@@ -195,13 +208,15 @@ class QualityAnalyzer:
if accuracy < 100 and issues:
suggestions.extend(issues[:3]) # Top 3 issues
self.metrics.append(QualityMetric(
name="Accuracy",
value=accuracy,
level=level,
description=f"Documentation accuracy: {accuracy:.1f}%",
suggestions=suggestions
))
self.metrics.append(
QualityMetric(
name="Accuracy",
value=accuracy,
level=level,
description=f"Documentation accuracy: {accuracy:.1f}%",
suggestions=suggestions,
)
)
return accuracy
@@ -234,13 +249,13 @@ class QualityAnalyzer:
# Check for specific types (20 points each)
ref_names = [f.stem.lower() for f in ref_files]
if any('getting' in name or 'start' in name for name in ref_names):
if any("getting" in name or "start" in name for name in ref_names):
score += 20
if any('api' in name or 'reference' in name for name in ref_names):
if any("api" in name or "reference" in name for name in ref_names):
score += 20
if any('example' in name or 'tutorial' in name for name in ref_names):
if any("example" in name or "tutorial" in name for name in ref_names):
score += 20
# Has diverse content (10 points)
@@ -258,13 +273,15 @@ class QualityAnalyzer:
suggestions.append("Add API reference documentation")
suggestions.append("Expand documentation coverage")
self.metrics.append(QualityMetric(
name="Coverage",
value=coverage,
level=level,
description=f"Documentation coverage: {coverage:.1f}%",
suggestions=suggestions
))
self.metrics.append(
QualityMetric(
name="Coverage",
value=coverage,
level=level,
description=f"Documentation coverage: {coverage:.1f}%",
suggestions=suggestions,
)
)
return coverage
@@ -308,56 +325,54 @@ class QualityAnalyzer:
if health < 100:
suggestions.extend(issues[:3])
self.metrics.append(QualityMetric(
name="Health",
value=health,
level=level,
description=f"Skill health: {health:.1f}%",
suggestions=suggestions
))
self.metrics.append(
QualityMetric(
name="Health",
value=health,
level=level,
description=f"Skill health: {health:.1f}%",
suggestions=suggestions,
)
)
return health
def calculate_statistics(self) -> dict[str, Any]:
"""Calculate skill statistics."""
stats = {
'total_files': 0,
'total_size_bytes': 0,
'markdown_files': 0,
'reference_files': 0,
'total_characters': 0,
'total_words': 0
"total_files": 0,
"total_size_bytes": 0,
"markdown_files": 0,
"reference_files": 0,
"total_characters": 0,
"total_words": 0,
}
# Count files and sizes
for md_file in self.skill_dir.rglob("*.md"):
stats['total_files'] += 1
stats['markdown_files'] += 1
stats["total_files"] += 1
stats["markdown_files"] += 1
size = md_file.stat().st_size
stats['total_size_bytes'] += size
stats["total_size_bytes"] += size
# Count words
try:
content = md_file.read_text(encoding="utf-8")
stats['total_characters'] += len(content)
stats['total_words'] += len(content.split())
stats["total_characters"] += len(content)
stats["total_words"] += len(content.split())
except Exception:
pass
# Count references
refs_dir = self.skill_dir / "references"
if refs_dir.exists():
stats['reference_files'] = len(list(refs_dir.glob("*.md")))
stats["reference_files"] = len(list(refs_dir.glob("*.md")))
self.statistics = stats
return stats
def calculate_overall_score(
self,
completeness: float,
accuracy: float,
coverage: float,
health: float
self, completeness: float, accuracy: float, coverage: float, health: float
) -> QualityScore:
"""
Calculate overall quality score.
@@ -368,15 +383,10 @@ class QualityAnalyzer:
- Coverage: 25%
- Health: 20%
"""
total = (
completeness * 0.30 +
accuracy * 0.25 +
coverage * 0.25 +
health * 0.20
)
total = completeness * 0.30 + accuracy * 0.25 + coverage * 0.25 + health * 0.20
# Determine grade
grade = 'F'
grade = "F"
for g, threshold in self.GRADE_THRESHOLDS.items():
if total >= threshold:
grade = g
@@ -388,7 +398,7 @@ class QualityAnalyzer:
accuracy=accuracy,
coverage=coverage,
health=health,
grade=grade
grade=grade,
)
def generate_recommendations(self, score: QualityScore) -> list[str]:
@@ -431,9 +441,7 @@ class QualityAnalyzer:
health = self.analyze_health()
# Calculate overall score
overall_score = self.calculate_overall_score(
completeness, accuracy, coverage, health
)
overall_score = self.calculate_overall_score(completeness, accuracy, coverage, health)
# Calculate statistics
stats = self.calculate_statistics()
@@ -447,7 +455,7 @@ class QualityAnalyzer:
overall_score=overall_score,
metrics=self.metrics,
statistics=stats,
recommendations=recommendations
recommendations=recommendations,
)
def format_report(self, report: QualityReport) -> str:
@@ -484,7 +492,7 @@ class QualityAnalyzer:
MetricLevel.INFO: "✅",
MetricLevel.WARNING: "⚠️",
MetricLevel.ERROR: "❌",
MetricLevel.CRITICAL: "🔴"
MetricLevel.CRITICAL: "🔴",
}.get(metric.level, "ℹ️")
lines.append(f" {icon} {metric.name}: {metric.value:.1f}%")
@@ -553,4 +561,5 @@ def main():
if __name__ == "__main__":
import sys
sys.exit(main())