agent-launcher-orchest…
Use when a user wants to build, launch, grade, or schedule a Claude Managed Agent (CMA) in their own Anthropic account — "build me an agent", "launch this as a…
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions
$ npx -y skills add alirezarezvani/claude-skills --skill cto-advisor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/cto-advisorContext preview
The summary Claude sees to decide when to auto-load this skill.
Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions
name: "cto-advisor" description: "Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. 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." license: MIT metadata: version: 2.0.0 author: Alireza Rezvani category: c-level domain: cto-leadership updated: 2026-03-05 python-tools: tech_debt_analyzer.py, team_scaling_calculator.py frameworks: architecture-decisions, engineering-metrics, technology-evaluation
Technical leadership frameworks for architecture, engineering teams, technology strategy, and technical decision-making.
CTO, chief technology officer, tech debt, technical debt, architecture, engineering metrics, DORA, team scaling, technology evaluation, build vs buy, cloud migration, platform engineering, AI/ML strategy, system design, incident response, engineering culture
python scripts/tech_debt_analyzer.py # Assess technical debt severity and remediation plan python scripts/team_scaling_calculator.py # Model engineering team growth and cost
Align technology investments with business priorities.
**Strategy components:**
See `references/technology_evaluation_framework.md` for the full evaluation framework.
Scale the engineering org's productivity — not individual output.
**Scaling engineering:**
**Culture:**
See `references/engineering_metrics.md` for DORA metrics and the engineering health dashboard.
Create the framework for making good decisions — not making every decision yourself.
**Architecture Decision Records (ADRs):**
See `references/architecture_decision_records.md` for ADR templates and the decision review process.
Every vendor is a dependency. Every dependency is a risk.
**Evaluation criteria:** Does it solve a real problem? Can we migrate away? Is the vendor stable? What's the total cost (license + integration + maintenance)?
Incident response, security breaches, major outages, data loss.
**Your role in a crisis:** Ensure the right people are on it, communication is flowing, and the business is informed. Post-crisis: blameless retrospective within 48 hours.
**Step 1 — Run the analyzer**
python scripts/tech_debt_analyzer.py --output report.json
**Step 2 — Interpret results** The analyzer produces a severity-scored inventory. Review each item against:
**Step 3 — Build a prioritized remediation plan** Sort by: `(Severity × Blast Radius) / Cost-to-fix` — highest score = fix first. Group items into: (a) immediate sprint, (b) next quarter, (c) tracked backlog.
**Step 4 — Validate before presenting to stakeholders**
**Example output — Tech Debt Inventory:**
Item | Severity | Cost-to-Fix | Blast Radius | Priority Score ----------------------|----------|-------------|--------------|--------------- Auth service (v1 API) | P1 | 8 days | 6 services | HIGH Unindexed DB queries | P2 | 3 days | 2 services | MEDIUM Legacy deploy scripts | P3 | 5 days | 1 service | LOW
---
**Step 1 — Identify the decision** Trigger an ADR when: the decision affects more than one team, is hard to reverse, or has cost/risk implications > 1 sprint of effort.
**Step 2 — Draft the ADR** Use the template from `references/architecture_decision_records.md`:
Title: [Short noun phrase] Status: Proposed | Accepted | Superseded Context: What is the problem? What constraints exist? Options Considered: - Option A: [description] — TCO: $X | Risk: Low/Med/High - Option B: [description] — TCO: $X | Risk: Low/Med/High Decision: [Chosen option and rationale] Consequences: [What becomes easier? What becomes harder?]
**Step 3 — Validation checkpoint (before finalizing)**
388 production-ready Claude Code skills, plugins, and agent skills for 13 AI coding tools. The most comprehensive open-source library of Claude Code skills and agent plugins — also works with OpenAI Codex, Gemini CLI, Cursor, and 9 more coding agents.
Repo: alirezarezvani/claude-skills
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