CTO Advisor

CTO Advisor is a portable, text-based skill from Alireza Rezvani's official claude-skills repository. The initially registered source at c-level-advisor/cto-advisor is no longer reachable. In commit 1851c8f the provider moved this skill, its references, and its Python tools to c-level-advisor/skills/cto-advisor. That canonical directory contains SKILL.md, three reference files, and the two named tools tech_debt_analyzer.py and team_scaling_calculator.py. This entry describes the current source rather than the removed registry path. The repository and the skill identify the MIT license. The source state was reviewed on September 10, 2026.

Purpose and Working Model

According to the provider, the skill gives a compatible coding agent a framework for technical leadership work. It connects technology and architecture decisions to business priorities, treats technical debt as a risk to manage, and supports planning for a growing engineering organization. For architecture decisions, the source recommends Architecture Decision Records that capture context, considered options, the decision, consequences, and later replacement. The architecture_decision_records.md reference adds templates, decision drivers, and examples covering monoliths, services, data stores, infrastructure, and development practices. The result is an auditable rationale, not an automatic architecture review.

Technical Debt, Selection, and Scaling

The source describes a workflow that inventories technical debt by severity, remediation effort, and affected scope. The tech_debt_analyzer.py tool accepts structured system data, calculates weighted categories, and produces prioritized actions. It is a heuristic analysis aid: its defaults, thresholds, and recommendations must be checked against measured evidence, team knowledge, and security requirements. The skill also covers build-versus-buy decisions, vendor dependencies, migration paths, total cost of ownership, and technology-radar questions. The technology_evaluation_framework.md reference makes evaluation factors and option comparison explicit. For team scaling, team_scaling_calculator.py provides a reproducible model for growth, roles, structure, and capacity; it is not a substitute for workforce planning, budget approval, or employment-law review.

Engineering and DORA Metrics

The engineering_metrics.md reference combines DORA metrics with a wider engineering-health dashboard. The source names deployment frequency, lead time for changes, change failure rate, and mean time to restore as important delivery and stability indicators. It also discusses technical debt, availability, performance, team health, and cloud cost. These measures are intended to reveal trends and system conditions, not to rank individual people. DORA metrics require clear definitions and context; this skill is neither a DORA certification nor a telemetry system. Teams must define events, time windows, service boundaries, and exclusions consistently for their own environment.

Boundaries and Safe Use

Without additional tools, the skill does not change cloud resources, deploy software, or access production systems. Its scripts read input files and produce reports; operators must review target paths, file permissions, and output destinations before running them. Advice about architecture, team size, technology selection, and metric targets is working material, not a guarantee of cost, reliability, or business outcomes. Confidential source code, internal metrics, credentials, and secrets must not be placed in prompts or reports. Local Python execution does not automatically prevent context from being sent to the selected model provider. The skill is identified for Claude Code; other agents need compatible skill or instruction integration. The MIT license permits use under the original terms, but does not replace review of third-party material included in a project. The provider path, actual files, license, and installation guidance were checked against official repository sources.