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Get Started Free →Inspect codebases: LOC, languages, ratios via pygount.
.claude/skills/hezaohezao-codebase-inspection/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 735% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 22% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 2% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 15% | 0% |
Analyze repositories for lines of code, language breakdown, file counts, and code-vs-comment ratios using pygount.
bashpip install pygount
bashcd /path/to/repo pygount --format=summary \ --folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.next,.tox,.eggs,*.egg-info" \ .
IMPORTANT: Always use --folders-to-skip to exclude dependency/build directories, otherwise pygount will crawl them and take a very long time.
bash# Python project --folders-to-skip=".git,__pycache__,venv,.venv,.tox,.eggs,*.egg-info,.pytest_cache,.mypy_cache,.ruff_cache" # Node.js project --folders-to-skip=".git,node_modules,dist,build,.next,.cache,coverage" # General (safe default) --folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.tox,.eggs,*.egg-info,.pytest_cache,.mypy_cache"
bashpygount --format=summary \ --folders-to-skip=".git,node_modules,.venv,__pycache__" \ --names-to-skip="*.pyc,*.pyo,*.so,*.dylib" \ /path/to/repo
bashpygount --format=summary /path/to/repo 2>/dev/null | grep -E "^\s+\w" | sort -t$'\t' -k2 -rn
bashpygount --format=json \ --folders-to-skip=".git,node_modules,.venv,__pycache__" \ /path/to/repo > codebase_stats.json python3 -c " import json with open('codebase_stats.json') as f: data = json.load(f) # Aggregate by language from collections import defaultdict by_lang = defaultdict(lambda: {'code': 0, 'files': 0}) for entry in data: lang = entry.get('language', 'unknown') by_lang[lang]['code'] += entry.get('code', 0) by_lang[lang]['files'] += 1 for lang, stats in sorted(by_lang.items(), key=lambda x: -x[1]['code']): print(f'{lang:20s} {stats[\"code\"]:8d} lines {stats[\"files\"]:4d} files') "
If pygount isn't available, use find + wc:
bash# Count lines in all Python files (excluding venvs) find . -name "*.py" -not -path "*/venv/*" -not -path "*/.venv/*" -not -path "*/__pycache__/*" | xargs wc -l | tail -1 # Count by language echo "Python: $(find . -name '*.py' -not -path '*/.venv/*' | xargs wc -l 2>/dev/null | tail -1)" echo "JavaScript: $(find . -name '*.js' -not -path '*/node_modules/*' | xargs wc -l 2>/dev/null | tail -1)" echo "TypeScript: $(find . -name '*.ts' -not -path '*/node_modules/*' | xargs wc -l 2>/dev/null | tail -1)"
bash# Count files by extension find . -type f -not -path "*/.git/*" -not -path "*/node_modules/*" -not -path "*/.venv/*" | \ sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20
node_modules, venv, .venv,__pycache__, dist, build — otherwise pygount hangs or counts millions of irrelevant lines.
find + wc doesn't. Use--names-to-skip for pygount, or filter with grep -I for find.
*.min.js, *_pb2.py, auto-generated code inflatescounts. Exclude with --names-to-skip.
--encoding=utf-8or --encoding=chardet for mixed-encoding repos.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 7,698 | 8,482 | +10% | 1 | 1 | 0% | 349 | 2,915 | +735% | 0 | 0 | — |
case-02 | fail→fail | 12,065 | 6,213 | -49% | 1 | 1 | 0% | 1,946 | 1,416 | -27% | 0 | 0 | — |
case-03 | fail→fail | 11,450 | 6,056 | -47% | 1 | 1 | 0% | 311 | 1,780 | +472% | 0 | 0 | — |
case-04 | pass→pass | 18,234 | 18,792 | +3% | 1 | 1 | 0% | 3,172 | 4,499 | +42% | 0 | 0 | — |
case-05 | pass→pass | 7,181 | 6,618 | -8% | 1 | 1 | 0% | 1,061 | 2,226 | +110% | 0 | 0 | — |
case-06 | pass→pass | 11,233 | 12,432 | +11% | 1 | 1 | 0% | 1,648 | 2,504 | +52% | 0 | 0 | — |
case-07 | fail→pass | 9,968 | 8,739 | -12% | 1 | 1 | 0% | 1,714 | 2,086 | +22% | 0 | 0 | — |
case-08 | fail→pass | 10,549 | 5,859 | -44% | 1 | 1 | 0% | 1,812 | 2,187 | +21% | 0 | 0 | — |
case-09 | fail→pass | 15,447 | 5,920 | -62% | 1 | 1 | 0% | 2,190 | 2,236 | +2% | 0 | 0 | — |
case-10 | fail→pass | 27,125 | 11,776 | -57% | 1 | 1 | 0% | 3,009 | 3,466 | +15% | 0 | 0 | — |
case-11 | pass→pass | 21,343 | 10,568 | -50% | 1 | 1 | 0% | 2,690 | 3,054 | +14% | 0 | 0 | — |
case-12 | pass→pass | 14,770 | 32,202 | +118% | 1 | 1 | 0% | 2,703 | 4,019 | +49% | 0 | 0 | — |
case-13 | fail→pass | 24,193 | 12,329 | -49% | 1 | 1 | 0% | 2,149 | 3,363 | +56% | 0 | 0 | — |
case-14 | fail→pass | 26,360 | 7,562 | -71% | 1 | 1 | 0% | 2,198 | 2,391 | +9% | 0 | 0 | — |
case-15 | fail→pass | 16,378 | 36,099 | +120% | 1 | 1 | 0% | 2,982 | 7,999 | +168% | 0 | 0 | — |
case-16 | fail→pass | 22,323 | 4,815 | -78% | 1 | 1 | 0% | 1,144 | 1,844 | +61% | 0 | 0 | — |
case-17 | fail→pass | 8,046 | 3,598 | -55% | 1 | 1 | 0% | 1,535 | 1,768 | +15% | 0 | 0 | — |
case-18 | fail→pass | 26,475 | 7,573 | -71% | 1 | 1 | 0% | 1,300 | 2,199 | +69% | 0 | 0 | — |
case-19 | fail→fail | 11,886 | 9,060 | -24% | 1 | 1 | 0% | 2,053 | 2,912 | +42% | 0 | 0 | — |
case-20 | pass→pass | 17,041 | 13,402 | -21% | 1 | 1 | 0% | 2,596 | 3,328 | +28% | 0 | 0 | — |
case-21 | pass→pass | 17,618 | 2,051 | -88% | 1 | 1 | 0% | 1,171 | 1,378 | +18% | 0 | 0 | — |
case-22 | pass→pass | 16,032 | 8,225 | -49% | 1 | 1 | 0% | 2,993 | 2,593 | -13% | 0 | 0 | — |
case-23 | fail→pass | 12,679 | 5,046 | -60% | 1 | 1 | 0% | 2,165 | 1,931 | -11% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 18 counted toward the lift figure. The other 5 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +52 percentage points is the difference between those two pass rates over the 18 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.