Engineering EvaluationTCOArchitecture

Tech Stack Evaluator

Technology stack evaluation with TCO analysis, security assessment, and scoring.

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Real Examples Get Started Models & Context

Real Conversations

See how the Tech Stack Evaluator skill responds to actual requests. These are representative examples of what your AI agent will produce.

You

Building a B2B SaaS dashboard — data-heavy, lots of forms, real-time updates, 4-engineer team. Should we use Next.js App Router or Remix?

Agent

Evaluation: Next.js App Router vs Remix

Criterion	Next.js App Router	Remix
Data loading	RSC + Server Actions	Loaders + Actions (nested)
Form handling	Server Actions (new, less battle-tested)	Native — excellent, progressive enhancement
Real-time	Requires separate WebSocket/SSE	Requires separate WebSocket/SSE
Ecosystem	Massive — Vercel, shadcn, next-auth	Smaller but growing
Learning curve	RSC mental model steep	More aligned with web standards
Deployment flexibility	Any Node/edge	Any Node/edge
TCO (hosting)	Vercel optimal, self-host complex	Self-host straightforward

For your use case — recommendation: Next.js App Router

Why:

Data-heavy dashboards benefit from RSC — render tables server-side, ship zero client JS for static content
4-engineer team: larger hiring pool for Next.js, more Stack Overflow answers, more tutorials
shadcn/ui component library is built for Next.js and dramatically speeds up dashboard UI
Real-time: use SSE or Pusher with either framework — not a differentiator

Where Remix would win: If your forms are critical path (e.g., input-heavy workflow tools) and you want progressive enhancement out of the box, Remix's form handling is genuinely superior.

TCO estimate (2 engineers, 12 months):

Next.js on Vercel: ~$1,200/year (Pro plan)
Next.js self-hosted on Railway/Fly.io: ~$600/year
Remix on Fly.io: ~$400/year

Recommendation: Next.js App Router + shadcn/ui + Supabase for the DB layer. This stack has the most momentum and the most production dashboards as reference.

You

We need to process 50,000 events/second from IoT sensors. Evaluating Apache Kafka vs AWS SQS + SNS. Running on AWS, 6-person team, no Kafka experience.

Agent

Evaluation: Kafka vs SQS/SNS at 50k msg/sec

Criterion	Apache Kafka (MSK)	SQS + SNS
Throughput	Millions/sec	~3,000/sec per queue
Message replay	Yes — configurable retention	No (once consumed, gone)
Ordering	Per-partition guarantee	FIFO queues only, limited
Ops complexity	High — brokers, ZK/KRaft, monitoring	Near-zero (managed)
Cost at 50k msg/sec	~$800-1,200/month (MSK)	~$2,200/month (SQS pricing)
Team ramp-up	2-4 weeks	1-2 days

Verdict: MSK (Managed Kafka) for your throughput, with a caveat

50,000 msg/sec exceeds SQS's practical single-queue throughput (SQS FIFO caps at 3k/sec; standard is higher but unordered). You'd need 20+ queues and fan-out logic — which is more complexity than Kafka anyway.

MSK sizing for 50k msg/sec:

- 3 broker cluster, kafka.m5.2xlarge (8 vCPU, 32GB)
- 6 partitions per topic (start here, scale out if needed)
- Replication factor: 3
- Estimated cost: ~$900/month

The real risk is your team's Kafka inexperience. Mitigation plan:

Start with MSK Serverless (no broker management) — pay per GB, learn the API
Migrate to provisioned MSK when you hit $500/month on Serverless
Allocate 2 weeks for the team to complete Confluent's free Kafka training before production

Alternative worth considering: Amazon Kinesis Data Streams — managed, AWS-native, handles your throughput, simpler ops than Kafka. Less flexible (7-day max retention, no compaction) but fits 80% of IoT use cases.

Get Started

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Skills are designed for AI coding agents (Claude Code, Cursor, Windsurf) and IDE-based workflows where the agent can read files, run scripts, and act on your codebase. Web-based AI can use the knowledge and frameworks, but won't have tool access.

Models & Context

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Recommended Models

Best

Claude Opus 4 Claude Sonnet 4 GPT-4.1 Gemini 2.5 Pro Grok 3 Kimi K2

Good

Claude Haiku 4.5 GPT-4.1 mini Gemini 2.5 Flash Grok 3 mini

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Context Window

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8K Skill only

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Pro tips for best results

1

Be specific

Include numbers — users, budget, RPS — so the skill can size the architecture.

2

Share constraints

Compliance needs, team size, and existing stack all improve the output.

3

Iterate

Start with a high-level design, then ask follow-ups for IaC, cost analysis, or security review.

4

Combine skills

Pair with companion skills below for end-to-end coverage.

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