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From agi-super-team
Technical leadership guidance for engineering teams: tech debt analysis, team scaling calculator, ADR templates, DORA metrics, and technology evaluation frameworks.
How this skill is triggered — by the user, by Claude, or both
Slash command
/agi-super-team:cto-advisorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Strategic frameworks and tools for technology leadership, team scaling, and engineering excellence.
Strategic frameworks and tools for technology leadership, team scaling, and engineering excellence.
CTO, chief technology officer, technical leadership, tech debt, technical debt, engineering team, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, ADR, architecture decision records, technology strategy, engineering leadership, engineering organization, team structure, hiring plan, technical strategy, vendor evaluation, technology selection
python scripts/tech_debt_analyzer.py
Analyzes system architecture and provides prioritized debt reduction plan.
python scripts/team_scaling_calculator.py
Calculates optimal hiring plan and team structure for growth.
Review references/architecture_decision_records.md for ADR templates and examples.
Use framework in references/technology_evaluation_framework.md for vendor selection.
Implement KPIs from references/engineering_metrics.md for team performance tracking.
# Assess current debt
python scripts/tech_debt_analyzer.py
# Allocate capacity
- Critical debt: 40% capacity
- High debt: 25% capacity
- Medium debt: 15% capacity
- Low debt: Ongoing maintenance
# Calculate scaling needs
python scripts/team_scaling_calculator.py
# Key ratios to maintain:
- Manager:Engineer = 1:8
- Senior:Mid:Junior = 3:4:2
- Product:Engineering = 1:10
- QA:Engineering = 1.5:10
Use ADR template from references/architecture_decision_records.md:
Follow framework in references/technology_evaluation_framework.md:
From references/engineering_metrics.md:
DORA Metrics (Deploy to production targets):
Quality Metrics:
Team Health:
Immediate (0-15 min):
Short-term (15-60 min):
Resolution (1-24 hours):
Post-mortem (48-72 hours):
Monthly:
Quarterly:
1. Executive Summary (1 slide)
2. Current State Assessment (2 slides)
3. Vision & Strategy (2 slides)
4. Roadmap & Milestones (3 slides)
5. Investment Required (1 slide)
6. Risks & Mitigation (1 slide)
7. Success Metrics (1 slide)
1. Wins & Recognition (5 min)
2. Metrics Review (5 min)
3. Strategic Updates (10 min)
4. Demo/Deep Dive (15 min)
5. Q&A (10 min)
Subject: Engineering Update - [Month]
Highlights:
• [Major achievement]
• [Key metric improvement]
• [Strategic progress]
Challenges:
• [Issue and mitigation]
Next Month:
• [Priority 1]
• [Priority 2]
Detailed metrics attached.
Books:
Frameworks:
Communities:
✅ Technical Excellence
✅ Team Success
✅ Business Impact
⚠️ Increasing technical debt
⚠️ Rising attrition rate
⚠️ Slowing velocity
⚠️ Growing incidents
⚠️ Team morale declining
⚠️ Budget overruns
⚠️ Vendor dependencies
⚠️ Security vulnerabilities
Analyzes system architecture for technical debt across 5 categories (architecture, code quality, infrastructure, security, performance). Calculates weighted debt scores, prioritizes reduction actions, estimates effort, and assesses risk levels.
python scripts/tech_debt_analyzer.py --input system_config.json --json
python scripts/tech_debt_analyzer.py --input system_config.json
| Flag | Type | Description |
|---|---|---|
--input | optional | Path to JSON file with system configuration (category indicators scored 0-100, team size, criticality, business context). Uses built-in example if omitted |
--json | optional | Output in JSON format instead of human-readable text |
Calculates optimal engineering team scaling plans including hiring timeline, role distribution, team structure design, budget projections, and risk assessment. Applies Brooks' Law and Conway's Law factors.
python scripts/team_scaling_calculator.py --input team_data.json --json
python scripts/team_scaling_calculator.py --input team_data.json
| Flag | Type | Description |
|---|---|---|
--input | optional | Path to JSON file with current state (headcount, roles, velocity) and growth targets (target headcount, timeline). Uses built-in example if omitted |
--json | optional | Output in JSON format instead of human-readable text |
| Problem | Likely Cause | Resolution |
|---|---|---|
| Tech debt score increasing despite dedicated sprints | Debt reduction not keeping pace with new debt creation | Implement debt prevention gates (code review, architecture review); track debt creation rate alongside reduction rate |
| DORA metrics improving but customer satisfaction declining | Shipping faster but not shipping the right things | Add customer-impact metrics alongside DORA; review feature adoption rates; reconnect with product team on priorities |
| Team scaling plan keeps missing hiring targets | Unrealistic timeline, insufficient recruiting capacity, or poor employer brand | Adjust timeline using 25% max quarterly growth rate; add recruiting resources (1 per 50 annual hires); invest in employer brand |
| Architecture decisions not documented or followed | No ADR process or ADRs created but not referenced | Implement lightweight ADR template; make ADR review part of design review; link ADRs to relevant code |
| Engineering team morale declining during rapid growth | Culture dilution, unclear expectations, or insufficient onboarding | Implement structured onboarding; maintain 1:8 manager ratio; run quarterly team health surveys |
| Vendor lock-in creating strategic risk | No evaluation framework or over-reliance on single vendor | Run technology evaluation for critical vendors; implement abstraction layers; maintain exit strategies |
In scope: Technology strategy and vision, technical debt assessment and reduction planning, engineering team scaling and structure design, architecture governance (ADRs, design reviews), vendor management and evaluation, engineering metrics (DORA, quality, team health), crisis management (incident response, security breach, data loss), stakeholder management and board reporting, and strategic initiatives (cloud migration, platform engineering, AI/ML integration).
Out of scope: Hands-on coding or code review (use engineering/ skills), product feature prioritization (use cpo-advisor), security architecture and compliance (use ciso-advisor or ra-qm-team/), HR policy and compensation design (use chro-advisor or hr-operations/), and financial planning for engineering budget (use cfo-advisor). Tools analyze engineering data snapshots; continuous metrics tracking requires integration with DevOps platforms.
Limitations: Tech debt scoring depends on self-reported indicator data; automated code analysis tools provide more objective measures. Team scaling budget projections use average salary bands that vary significantly by location, seniority mix, and market conditions. DORA benchmarks assume standard software delivery practices; hardware or embedded systems teams may need different targets.
npx claudepluginhub aaaaqwq/agi-super-team --plugin agi-super-teamDelivers CTO-level guidance: tech debt analyzer, team scaling calculator, DORA/engineering metrics, technology evaluation frameworks, ADR templates. For architecture decisions, strategy, and team growth.
Provides technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, DORA metrics, ADR templates, and technology evaluation tools.
Strategic CTO advisor with structured sub-commands. Helps technical leaders navigate architecture decisions, organizational design, stakeholder communication, and AI-era challenges. Each sub-command applies a specific framework and produces a concrete artifact. Triggers: cto, pivot cost, hire case, decision map, tech strategy, team health, board prep, ai audit.