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scripts-assess-production

#!/usr/bin/env python3 """​

title: "Assess Production" component_type: script version: "1.0.0" audience: contributor status: stable summary: "CODITECT Production Readiness Assessment =========================================" keywords: ['analysis', 'api', 'assess', 'deployment', 'production'] tokens: ~500 created: 2025-12-22 updated: 2025-12-22 script_name: "assess-production.py" language: python executable: true usage: "python3 scripts/assess-production.py [options]" python_version: "3.10+" dependencies: [] modifies_files: false network_access: false requires_auth: false​

CODITECT Production Readiness Assessment

STATUS: STUB - Not yet implemented VERSION: 0.1.0 (placeholder) AUTHOR: CODITECT Core Team

DESCRIPTION: Comprehensive production readiness assessment that evaluates a project against CODITECT production standards across multiple dimensions: code quality, testing, security, documentation, and operations.

PURPOSE: - Score production readiness (0-100) - Identify gaps against production standards - Generate actionable remediation roadmap - Track readiness improvements over time - Validate before production deployments

EXPECTED INPUTS: --paths : Project paths to assess --standards : Standards profile (basic, enterprise, critical) --output : Assessment report output --threshold : Minimum score to pass --categories : Categories to assess (all, code, tests, security, docs, ops)

EXPECTED OUTPUTS: - production-assessment.json with: { "overall_score": 85, "ready_for_production": true/false, "categories": { "code_quality": {"score": 90, "findings": [...]}, "test_coverage": {"score": 85, "findings": [...]}, "security": {"score": 80, "findings": [...]}, "documentation": {"score": 75, "findings": [...]}, "operations": {"score": 90, "findings": [...]} }, "blockers": [], "recommendations": [] }

ASSESSMENT CRITERIA: Code Quality: Linting, complexity, duplication, patterns Testing: Coverage, test types, CI integration Security: Vulnerabilities, secrets, dependencies Documentation: README, API docs, runbooks Operations: Monitoring, logging, deployment, rollback

IMPLEMENTATION REQUIREMENTS: 1. Multi-tool integration (test-suite, security-audit, lint-docs) 2. Weighted scoring algorithm 3. Standards profile configuration 4. Gap analysis engine 5. Remediation prioritization 6. Historical tracking

USAGE EXAMPLES: python scripts/assess-production.py python scripts/assess-production.py --standards enterprise --threshold 90 python scripts/assess-production.py --categories security,tests

SEE ALSO: - commands/production-cleanup.md - docs/PRODUCTION-STANDARDS.md """

import argparse import json import sys

def main(): parser = argparse.ArgumentParser( description='Production Readiness Assessment', epilog='Status: STUB - Implementation required' ) parser.add_argument('--paths', nargs='', default=['.']) parser.add_argument('--standards', default='basic', choices=['basic', 'enterprise', 'critical']) parser.add_argument('--output', default='production-assessment.json') parser.add_argument('--threshold', type=int, default=80) parser.add_argument('--categories', nargs='', default=['all'])

args = parser.parse_args()

print("CODITECT ASSESS-PRODUCTION - STUB")
print(f"Standards: {args.standards}, Threshold: {args.threshold}")

stub = {
    "status": "stub",
    "overall_score": 0,
    "ready_for_production": False,
    "message": "Assessment not yet implemented"
}
with open(args.output, 'w') as f:
    json.dump(stub, f, indent=2)

return 0

if name == 'main': sys.exit(main())