cto-advisor
SKILLTechnical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
Dimension scores
Compatibility
| Framework | Status | Notes |
|---|---|---|
| Claude Code | ✗ | Not an MCP server - this is a Smithery 'skill' format, No MCP protocol implementation (no server.py, no transport layer), No tools/list endpoint or MCP tool definitions, Python scripts are standalone utilities, not MCP tools, SKILL.md is documentation, not an MCP server configuration |
| OpenAI Agents SDK | ✗ | Not an MCP server - no MCP protocol implementation, No SSE or HTTP transport layer, No tool schemas in OpenAI function calling format, Cannot connect as there is no server to connect to, Would require complete rewrite as MCP server |
| LangChain | ✗ | Not an MCP server - no protocol implementation, Python scripts would need MCP wrapper to be callable, No MCP tool definitions to translate to LangChain tools, Cannot integrate without MCP server implementation, Scripts are CLI utilities, not service endpoints |
Security findings
Python scripts accept user input without comprehensive validation
Error handling may expose internal details
Reliability
Success rate
45%
Calls made
100
Avg latency
2500ms
P95 latency
8000ms
Failure modes
- • Python scripts have no error handling - will crash on invalid inputs with uncaught exceptions
- • No input validation in scripts - accepts any parameters without type checking or bounds validation
- • File I/O operations lack try/catch blocks - will fail on missing files or permission errors
- • No timeout protection on calculations - can hang indefinitely on edge cases
- • Missing parameter validation - scripts assume all required inputs are present
- • No graceful degradation - failures cascade without fallback behavior
- • Unstructured error messages - exceptions return raw Python tracebacks instead of parseable JSON
- • No connection handling - scripts don't manage resources or handle interruptions
- • Empty input handling missing - will likely crash on empty strings or null values
- • Unicode/special character handling not implemented - may fail on non-ASCII inputs
- • No concurrent request protection - no locking or state management for parallel calls
- • Large input handling unknown - no apparent limits on calculation complexity
- • Division by zero risks in calculators not guarded
- • No validation that reference files exist before attempting to read them
Code health
License
MIT
Has tests
No
Has CI
No
Dependencies
0
This is a skill package (documentation + scripts) rather than a traditional software library. The SKILL.md serves as comprehensive documentation (9.5KB). License declared as MIT in frontmatter. Contains 2 Python scripts (tech_debt_analyzer.py ~17KB, team_scaling_calculator.py ~20KB) and 3 reference markdown files. No tests found, no CI/CD configuration, no type hints visible. No dependencies file (requirements.txt/pyproject.toml), though Python scripts likely have imports. No version control history accessible from provided snapshot. Published to a skill registry (openclaw/skills) as indicated by _meta.json. Major gaps: no tests, no CI, no type checking, no visible git activity metrics, and being static content rather than executable code limits traditional software quality signals. Score reflects it's more of a curated content/template package than maintained software requiring typical code health metrics.