Review architecture and engineering growth plans through six questions covering capacity limits, technical debt, staffing, build-versus-buy costs, reliability, and security. Produce a structured verdict and three next steps before committing to major technical decisions.
/c-level-agents:cto-review [plan] — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy. Use when committing to an architecture, planning for 10x load, or weighing a rebuild against a vendor.
Review the instructions the agent will receive before you install.
Command: /c-level-agents:cto-review <plan>
Pressure-tests architecture and engineering scaling decisions. Six questions to surface the next scaling cliff before you hit it.
Where does the current architecture break, in terms of users / requests / data volume?
What's the top tech debt item, what's it costing per week, and when does it become blocking?
python ${CLAUDE_PLUGIN_ROOT}/vendor/c-level-advisor/cto-advisor/scripts/tech_debt_analyzer.py
For each open req, what's the ramp time and contribution model?
python ${CLAUDE_PLUGIN_ROOT}/vendor/c-level-advisor/cto-advisor/scripts/team_scaling_calculator.py
Why are we building this instead of buying it — and what's the 3-year TCO of each?
What are the SLOs for this system and what's the current error budget burn?
engineering/slo-architect for SLO design.What does this expose, and has cs-ciso-advisor signed off?
# CTO Review: <plan>
**Date:** YYYY-MM-DD
## Scaling Cliff
- Current capacity: <metric>
- Break point: <metric>
- Headroom: X months at current growth
## Tech Debt
- Top item: <description>
- Cost per week: $X or N eng-hours
- Blocking date estimate: <date>
## Team
- Open reqs: N
- Median ramp: X months
- Contribution model: <pairing / squad / area>
## Build vs Buy
- 3-year build TCO: $X
- 3-year buy TCO: $X
- Strategic fit: <core / context>
- Decision: BUILD | BUY
## Reliability
- SLO defined: yes / no
- Error budget burn: X% (target < Y%)
## Security
- cs-ciso sign-off: ✅ / ❌
## Verdict
🟢 SHIP | 🟡 SHARPEN | 🔴 BLOCK
## Next Steps
[3 concrete actions]
/c-level-agents:ciso-review — mandatory if data surface changes/c-level-agents:cfo-review — for build-vs-buy > $100K/c-level-agents:execute — quarterly plan/c-level-agents:boardroom — for architecture pivotscs-cto-advisorcto-advisor../../../engineering/slo-architect/Version: 1.0.0
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Audit web applications for accessibility issues against WCAG 2.2 Level A and AA, the web accessibility standards. Get framework-specific code fixes, contrast checks, verification steps, and reports, with options for automated checks in development pipelines.
Plan A/B tests that compare page variations, from headlines to pricing layouts. Define a hypothesis, choose success metrics, calculate sample size and duration, and prepare launch checks and results reports to support decisions.
Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.
Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.
Audit and improve content intended for citation in AI answers. Review evidence, author information, and structure, generate revised content and structured metadata, and keep a local record of observed citations across AI services.
Create signed records for consequential agent actions such as deployments, deletions, and payments. Decide which actions need evidence, record the agent, action, target, and policy, then verify the resulting certificate offline to detect later changes.