Technical 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.
Install with Tessl CLI
npx tessl i github:alirezarezvani/claude-skills --skill cto-advisorOverall
score
78%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that follows best practices. It provides specific tools and capabilities, includes comprehensive trigger terms covering both formal terminology and common abbreviations, and has an explicit 'Use when...' clause. The description clearly carves out a distinct niche for CTO/technical leadership concerns that won't conflict with general development skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and tools: 'tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates' along with specific use cases like 'assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions.' | 3 / 3 |
Completeness | Clearly answers both what (technical leadership guidance, specific tools like tech debt analyzer, team scaling calculator, etc.) AND when with explicit 'Use when...' clause listing specific scenarios and trigger terms. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, technology strategy.' Includes both formal terms and common abbreviations. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused on CTO-level technical leadership with distinct triggers like 'DORA metrics', 'ADR templates', 'team scaling calculator' that are unlikely to conflict with general coding or documentation skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a comprehensive CTO reference but suffers from verbosity and generic management advice that Claude already knows. The structure and progressive disclosure are well-executed with clear references to supporting files, but the actionability is limited by high-level guidance rather than concrete, executable examples. The skill would benefit significantly from trimming generic content and adding more specific, executable artifacts.
Suggestions
Remove generic management advice Claude already knows (e.g., 'conduct 1:1s weekly', 'set clear OKRs', book recommendations) to improve conciseness
Replace template outlines with complete, copy-paste ready templates (e.g., full ADR template, complete board update email)
Add validation checkpoints to workflows, especially for tech debt assessment (e.g., 'verify debt categorization with team leads before allocating capacity')
Provide example inputs/outputs for the Python scripts to make them more actionable without running them
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but includes significant content Claude already knows (basic CTO responsibilities, generic management advice like 'conduct 1:1s weekly', book recommendations). Many sections could be condensed or removed entirely. | 2 / 3 |
Actionability | References executable scripts (tech_debt_analyzer.py, team_scaling_calculator.py) which is good, but most content is high-level guidance rather than concrete, executable instructions. Templates are outlines rather than copy-paste ready artifacts. | 2 / 3 |
Workflow Clarity | Some workflows are sequenced (incident response, vendor evaluation) but lack validation checkpoints. The crisis management section has steps but no explicit verification points. Tech debt allocation mentions capacity percentages but no validation of outcomes. | 2 / 3 |
Progressive Disclosure | Good structure with clear references to external files (architecture_decision_records.md, technology_evaluation_framework.md, engineering_metrics.md). Quick Start section provides clear entry points, and content is organized into logical sections with one-level-deep references. | 3 / 3 |
Total | 9 / 12 Passed |
Validation
88%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 14 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_field | 'metadata' should map string keys to string values | Warning |
body_output_format | No obvious output/return/format terms detected; consider specifying expected outputs | Warning |
Total | 14 / 16 Passed | |
Table of Contents
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