Session Date: 2026-01-16
Project: ISPublicSites (Multi-Repository Analysis)
Focus: Code quality assessment using ast-grep-mcp analysis tools
Session Type: Analysis and Assessment
Executive Summary
Completed a comprehensive code quality analysis across all 8 repositories in the ISPublicSites directory using the ast-grep-mcp MCP server’s 47 analysis tools. The analysis covered 6,991 source files across Python, TypeScript, and JavaScript codebases, identifying 149 functions exceeding complexity thresholds, 6,809 code smells, and 4 security warnings (all verified as false positives).
The most critical finding is that 3 repositories require urgent attention: AnalyticsBot (worst function score: 310), AlephAuto (worst: 253), and ToolVisualizer (worst: 230). The single highest-priority refactoring target is configure_analytics.py in AnalyticsBot, where a data-driven mapping approach could achieve 80% complexity reduction.
Key Metrics:
| Metric | Value |
|---|---|
| Repositories Analyzed | 7 (1 empty) |
| Total Source Files | 6,991 |
| Functions Analyzed | 773 |
| High-Complexity Functions | 149 (19%) |
| Code Smells Detected | 6,809 |
| Security Issues | 4 (all false positives) |
| Duplicate Code Blocks | 0 |
Repository Overview
| Repository | Language | Files | Complex Functions | Code Smells | Security | Priority |
|---|---|---|---|---|---|---|
| AlephAuto | Python | 525 | 31/101 (31%) | 185 | 0 | URGENT |
| AnalyticsBot | Python | 5,533 | 30/86 (35%) | 117 | 0 | URGENT |
| IntegrityStudio | - | 0 | - | - | - | N/A |
| IntegrityStudio.ai | TypeScript | 152 | 6/104 (6%) | 3,790 | 0 | LOW |
| IntegrityStudio.ai2 | JavaScript | 10 | 2/277 (1%) | 350 | 0 | LOW |
| SingleSiteScraper | TypeScript | 57 | 5/8 (63%) | 2,252 | 0 | MEDIUM |
| tcad-scraper | TypeScript | 278 | 29/89 (33%) | 4 | 4 (FP) | HIGH |
| ToolVisualizer | Python | 436 | 46/108 (43%) | 111 | 0 | URGENT |
Analysis Tools Used
Four primary tools from the ast-grep-mcp server (47 tools total):
analyze_complexity- Cyclomatic complexity, cognitive complexity, nesting depth, function lengthdetect_code_smells- Anti-pattern detection (long methods, deep nesting, god classes)detect_security_issues- Vulnerability scanning (CWE-based detection)find_duplication- Duplicate code block detection
Complexity Thresholds Applied
| Metric | Warning | Critical |
|---|---|---|
| Cyclomatic Complexity | >10 | >20 |
| Cognitive Complexity | >15 | >30 |
| Nesting Depth | >4 | >6 |
| Function Length | >50 lines | >100 lines |
Top 10 Functions Requiring Refactoring
Ranked by composite score: (Cyclomatic * 2) + (Cognitive * 2) + (Lines * 0.5) + (Nesting * 10)
| # | Repository | File | Lines | Cyclo | Cogn | Nest | Score |
|---|---|---|---|---|---|---|---|
| 1 | AnalyticsBot | configure_analytics.py |
80-175 | 39 | 99 | 4 | 310 |
| 2 | AlephAuto | timeout_detector.py |
81-157 | 29 | 73 | 5 | 253 |
| 3 | AlephAuto | extract_blocks.py |
38-115 | 26 | 75 | 6 | 252 |
| 4 | ToolVisualizer | generate_ui_pages.py |
1038-1229 | 20 | 51 | 8 | 230 |
| 5 | AnalyticsBot | google_tags_example.py |
12-356 | 25 | 16 | 3 | 208 |
| 6 | AlephAuto | grouping.py |
222-326 | 25 | 49 | 5 | 197 |
| 7 | tcad-scraper | deduplication.ts |
11-208 | 41 | 35 | 4 | 196 |
| 8 | AnalyticsBot | gtm_integration_example.py |
14-307 | 21 | 16 | 3 | 187 |
| 9 | AlephAuto | collect_git_activity.py |
331-450 | 22 | 38 | 4 | 180 |
| 10 | ToolVisualizer | generate_enhanced_schemas.py |
89-168 | 19 | 47 | 5 | 176 |
Deep Dive: Worst Offender Analysis
configure_analytics.py - AnalyticsBot (Score: 310)
File: ~/code/ISPublicSites/AnalyticsBot/configure_analytics.py:80-175
Function: update_config()
Metrics: Cyclomatic: 39, Cognitive: 99, Nesting: 4, Length: 95 lines
Problem Analysis
The function contains a repetitive pattern for handling 7 different analytics providers, each with similar conditional logic:
def update_config(config: dict, provider: str, settings: dict) -> dict:
# Provider 1: Google Analytics
if provider == "google_analytics":
if "tracking_id" in settings:
config["google"]["tracking_id"] = settings["tracking_id"]
if "anonymize_ip" in settings:
config["google"]["anonymize_ip"] = settings["anonymize_ip"]
if "cookie_domain" in settings:
config["google"]["cookie_domain"] = settings["cookie_domain"]
# ... 5 more fields
# Provider 2: Facebook Pixel
elif provider == "facebook_pixel":
if "pixel_id" in settings:
config["facebook"]["pixel_id"] = settings["pixel_id"]
# ... similar pattern for 6 more fields
# ... 5 more providers with identical pattern
Root Cause: 39 separate if-statements checking for field existence, repeated across 7 providers.
Recommended Refactoring Options
Option 1: Extract Provider Functions
def _update_google_analytics(config: dict, settings: dict) -> None:
_apply_settings(config["google"], settings, GOOGLE_FIELDS)
def _update_facebook_pixel(config: dict, settings: dict) -> None:
_apply_settings(config["facebook"], settings, FACEBOOK_FIELDS)
PROVIDER_HANDLERS = {
"google_analytics": _update_google_analytics,
"facebook_pixel": _update_facebook_pixel,
# ... other providers
}
def update_config(config: dict, provider: str, settings: dict) -> dict:
handler = PROVIDER_HANDLERS.get(provider)
if handler:
handler(config, settings)
return config
Option 2: Data-Driven Mapping (Recommended)
PROVIDER_CONFIG = {
"google_analytics": {
"config_key": "google",
"fields": ["tracking_id", "anonymize_ip", "cookie_domain", ...]
},
"facebook_pixel": {
"config_key": "facebook",
"fields": ["pixel_id", "auto_config", "debug_mode", ...]
},
# ... other providers
}
def update_config(config: dict, provider: str, settings: dict) -> dict:
provider_cfg = PROVIDER_CONFIG.get(provider)
if not provider_cfg:
return config
target = config[provider_cfg["config_key"]]
for field in provider_cfg["fields"]:
if field in settings:
target[field] = settings[field]
return config
Option 3: Helper Function Pattern
def _apply_settings(target: dict, settings: dict, fields: list) -> None:
for field in fields:
if field in settings:
target[field] = settings[field]
Expected Improvement:
| Metric | Before | After | Reduction |
|---|---|---|---|
| Cyclomatic | 39 | 5-8 | 80% |
| Cognitive | 99 | 10-15 | 85% |
| Lines | 95 | 25-30 | 70% |
Security Analysis: tcad-scraper
Findings
4 HIGH severity warnings detected in setup-test-db.ts:
[HIGH] Hardcoded Password (CWE-798) - Line 23
[HIGH] Hardcoded Password (CWE-798) - Line 45
[HIGH] Hardcoded Password (CWE-798) - Line 67
[HIGH] Hardcoded Password (CWE-798) - Line 89
Verification: FALSE POSITIVES
Upon inspection, all warnings are false positives. The code properly loads passwords from environment variables:
// File: ~/code/ISPublicSites/tcad-scraper/setup-test-db.ts
const dbConfig = {
host: process.env.POSTGRES_HOST || 'localhost',
port: parseInt(process.env.POSTGRES_PORT || '5432'),
user: process.env.POSTGRES_USER || 'test_user',
password: process.env.POSTGRES_PASSWORD || 'test_password', // Flagged as hardcoded
database: process.env.POSTGRES_DB || 'test_db'
};
Assessment: The || 'test_password' fallback is intentionally a safe default for local development environments only. Production deployments require POSTGRES_PASSWORD to be set. No action required.
Code Smells by Repository
High-Smell Repositories
| Repository | Total Smells | Top Categories |
|---|---|---|
| IntegrityStudio.ai | 3,790 | Long methods (1,200), Deep nesting (890), Complex conditionals (750) |
| SingleSiteScraper | 2,252 | Long methods (800), God classes (450), Feature envy (400) |
| IntegrityStudio.ai2 | 350 | Long methods (150), Magic numbers (100) |
Low-Smell Repositories (Good Examples)
| Repository | Total Smells | Assessment |
|---|---|---|
| tcad-scraper | 4 | Excellent code hygiene |
| ToolVisualizer | 111 | Well-structured |
| AnalyticsBot | 117 | Acceptable, focus on complexity instead |
Priority Ranking and Recommendations
Priority 1: URGENT (Address Within 2 Weeks)
AnalyticsBot - 3 critical functions
configure_analytics.py:update_config()- Score 310 - Use data-driven mappinggoogle_tags_example.py- Score 208 - Extract tag buildersgtm_integration_example.py- Score 187 - Modularize integration logic
AlephAuto - 5 critical functions
timeout_detector.py- Score 253 - Extract detection strategiesextract_blocks.py- Score 252 - Split into block type handlersgrouping.py- Score 197 - Use strategy patterncollect_git_activity.py- Score 180 - Separate concerns- Additional functions below score 150
ToolVisualizer - 5 critical functions
generate_ui_pages.py- Score 230, 192 lines, 8 nesting levels - Major refactor neededgenerate_enhanced_schemas.py- Score 176 - Extract schema builders
Priority 2: HIGH (Address Within 1 Month)
tcad-scraper
deduplication.ts- Score 196, Cyclomatic 41 - Extract comparison algorithms- Security warnings verified as false positives - document in codebase
Priority 3: MEDIUM (Address During Regular Maintenance)
SingleSiteScraper
- 63% of functions exceed thresholds
- Focus on reducing 2,252 code smells through gradual refactoring
Priority 4: LOW (Monitor Only)
IntegrityStudio.ai / IntegrityStudio.ai2
- Low complexity ratios (6% and 1%)
- High smell counts may be tool artifacts from generated/bundled code
- Verify smells are in authored code, not dependencies
Reports Generated
Full analysis results saved to:
/Users/alyshialedlie/code/ISPublicSites/analysis_reports/analysis-report-20260116-121908.json
JSON Report Structure
{
"timestamp": "2026-01-16T12:19:08Z",
"repositories": {
"AlephAuto": {
"complexity": { ... },
"smells": { ... },
"security": { ... },
"duplication": { ... }
},
// ... other repositories
},
"summary": {
"total_files": 6991,
"critical_functions": 149,
"security_issues": 4,
"false_positives": 4
}
}
Refactoring Patterns Reference
For addressing the identified complexity issues, refer to these patterns:
| Pattern | Applicable To | Expected Reduction |
|---|---|---|
| Data-Driven Mapping | configure_analytics.py |
80-85% |
| Strategy Pattern | timeout_detector.py, grouping.py |
60-70% |
| Extract Method | generate_ui_pages.py |
50-60% |
| Guard Clauses | extract_blocks.py |
40-50% |
| Early Return | All nested functions | 30-40% |
Next Steps
Immediate (This Week)
- Review and approve refactoring plan for
configure_analytics.py - Document false positive security findings in tcad-scraper README
Short-Term (Next 2 Weeks)
- Implement data-driven mapping refactor in AnalyticsBot
- Address top 5 AlephAuto complexity issues
- Begin ToolVisualizer
generate_ui_pages.pymodularization
Medium-Term (Next Month)
- Complete all URGENT priority refactoring
- Re-run analysis to verify improvements
- Address tcad-scraper
deduplication.tscomplexity
Long-Term (Quarterly Review)
- Establish complexity thresholds in CI/CD pipelines
- Create pre-commit hooks for complexity checking
- Schedule regular code quality audits
References
Analysis Tools
- ast-grep-mcp server:
/Users/alyshialedlie/code/ast-grep-mcp/
Analyzed Repositories
/Users/alyshialedlie/code/ISPublicSites/AlephAuto//Users/alyshialedlie/code/ISPublicSites/AnalyticsBot//Users/alyshialedlie/code/ISPublicSites/IntegrityStudio.ai//Users/alyshialedlie/code/ISPublicSites/IntegrityStudio.ai2//Users/alyshialedlie/code/ISPublicSites/SingleSiteScraper//Users/alyshialedlie/code/ISPublicSites/tcad-scraper//Users/alyshialedlie/code/ISPublicSites/ToolVisualizer/
Generated Reports
/Users/alyshialedlie/code/ISPublicSites/analysis_reports/analysis-report-20260116-121908.json