Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/alirezarezvani/claude-cto-team/tech-stack-recommendernpx skills add alirezarezvani/claude-cto-team --skill tech-stack-recommendergit clone --depth 1 https://github.com/alirezarezvani/claude-cto-teamWrote 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/skills/alirezarezvani/claude-cto-team/tech-stack-recommender)<a href="https://agentmods.dev/skills/alirezarezvani/claude-cto-team/tech-stack-recommender"><img src="https://agentmods.dev/badge/skills/alirezarezvani/claude-cto-team/tech-stack-recommender.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.03760 |
| Opus 5 | $0.00017 | $0.01880 |
| Sonnet 5 | $0.00007 | $0.00752 |
| Haiku 4.5 | $0.00003 | $0.00376 |
Grade A, and why
tech-stack-recommender 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 5d 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 — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Stack Recommender
Provides structured recommendations for technology stack selection based on project requirements, team constraints, and business goals.
When to Use
- Starting a new project and need stack recommendations
- Evaluating technology options for specific use cases
- Comparing frameworks or languages for a project
- Assessing team readiness for a technology choice
- Planning technology migrations
Stack Selection Framework
Decision Inputs
┌───────────────────────────────────────────────────────────────────┐
│ STACK SELECTION INPUTS │
├───────────────────────────────────────────────────────────────────┤
│ │
│ Project Requirements Team Factors Business Constraints│
│ ──────────────────── ──────────── ────────────────── │
│ • Scale expectations • Current skills • Time to market │
│ • Performance needs • Learning capacity • Budget │
│ • Integration points • Team size • Hiring market │
│ • Compliance/Security • Experience level • Long-term support │
│ │
└───────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────┐
│ RECOMMENDATION │
│ Framework │
└─────────────────┘
Quick Stack Recommendations
By Project Type
| Project Type | Frontend | Backend | Database | Why |
|---|---|---|---|---|
| SaaS MVP | Next.js | Node.js/Express | PostgreSQL | Fast iteration, full-stack JS |
| E-commerce | Next.js | Node.js or Python | PostgreSQL + Redis | SEO, caching, transactions |
| Mobile App | React Native | Node.js/Python | PostgreSQL | Cross-platform, shared logic |
| Real-time App | React | Node.js + WebSocket | PostgreSQL + Redis | Event-driven, low latency |
| Data Platform | React | Python/FastAPI | PostgreSQL + ClickHouse | Data processing, analytics |
| Enterprise | React | Java/Spring or .NET | PostgreSQL/Oracle | Stability, enterprise support |
| ML Product | React | Python/FastAPI | PostgreSQL + Vector DB | ML ecosystem, inference |
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.
- 5d ago First seen · 448 lines · 35 tokens per session scan A 88bf2c8f35a3
tech-stack-recommender is a skill published in the GitHub repository alirezarezvani/claude-cto-team (112 stars, last pushed 8mo ago), licensed MIT. It adds 35 tokens to every session and 3,760 once invoked, about $0.0002 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 2026-08-30.
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../../../product-team/agile-product-owner/skills/agile-product-owner/SKILL.md.
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