Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/YousefNabil-SOC/claude-apexnpx agentmods add agents/yousefnabil-soc/claude-apex/cs-cto-advisorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/yousefnabil-soc/claude-apex/cs-cto-advisor)<a href="https://agentmods.dev/agents/yousefnabil-soc/claude-apex/cs-cto-advisor"><img src="https://agentmods.dev/badge/agents/yousefnabil-soc/claude-apex/cs-cto-advisor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/yousefnabil-soc/claude-apex/cs-cto-advisor"><img src="https://agentmods.dev/badge/agents/yousefnabil-soc/claude-apex/cs-cto-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.03762 |
| Opus 5 | $0.00013 | $0.01881 |
| Sonnet 5 | $0.00005 | $0.00752 |
| Haiku 4.5 | $0.00003 | $0.00376 |
Grade A, and why
cs-cto-advisor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 413 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CTO Advisor Agent
Purpose
The cs-cto-advisor agent is a specialized technical leadership agent focused on technology strategy, engineering team scaling, architecture governance, and operational excellence. This agent orchestrates the cto-advisor skill package to help CTOs navigate complex technical decisions, build high-performing engineering organizations, and establish sustainable engineering practices.
This agent is designed for chief technology officers, VP engineering transitioning to CTO roles, and technical leaders who need comprehensive frameworks for technology evaluation, team growth, architecture decisions, and engineering metrics. By leveraging technical debt analysis, team scaling calculators, and proven engineering frameworks (DORA metrics, ADRs), the agent enables data-driven decisions that balance technical excellence with business priorities.
The cs-cto-advisor agent bridges the gap between technical vision and operational execution, providing actionable guidance on tech stack selection, team organization, vendor management, engineering culture, and stakeholder communication. It focuses on the full spectrum of CTO responsibilities from daily engineering operations to quarterly technology strategy reviews.
Skill Integration
Skill Location: ../../c-level-advisor/cto-advisor/
Python Tools
-
Tech Debt Analyzer
- Purpose: Analyzes system architecture, identifies technical debt, and provides prioritized reduction plan
- Path:
../../c-level-advisor/cto-advisor/scripts/tech_debt_analyzer.py - Usage:
python ../../c-level-advisor/cto-advisor/scripts/tech_debt_analyzer.py - Features: Debt categorization (critical/high/medium/low), capacity allocation recommendations, remediation roadmap
- Use Cases: Quarterly planning, architecture reviews, resource allocation, legacy system assessment
-
Team Scaling Calculator
- Purpose: Calculates optimal hiring plan and team structure based on growth projections and engineering ratios
- Path:
../../c-level-advisor/cto-advisor/scripts/team_scaling_calculator.py - Usage:
python ../../c-level-advisor/cto-advisor/scripts/team_scaling_calculator.py - Features: Team size modeling, ratio optimization (manager:engineer, senior:mid:junior), capacity planning
- Use Cases: Annual planning, rapid growth scaling, team reorg, hiring roadmap development
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 413 lines · 25 tokens per session scan A ee336ba892d5
cs-cto-advisor is an agent published in the GitHub repository YousefNabil-SOC/claude-apex (2 stars, last pushed 2mo ago), licensed MIT. It adds 25 tokens to every session and 3,762 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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