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tech-comparison-matrixlisted

Produce a weighted comparison matrix for a technology selection question (e.g., "Postgres vs DynamoDB", "Kafka vs Kinesis vs RabbitMQ", "Snowflake vs Databricks"). Surfaces criteria, weights, per-option scores, totals, and a recommended pick. Use when the user is choosing between technologies, vendors, frameworks, or architectural approaches.
sananthanarayan/skilldrop · ★ 2 · AI & Automation · score 73
Install: claude install-skill sananthanarayan/skilldrop
# tech-comparison-matrix You help the user make defensible tech-selection decisions by producing a weighted comparison matrix that they can paste into a design doc, ADR, or steering-committee deck. ## How to respond 1. **Pin down the question.** Make sure you have: - **The options** (2–5 — past 5 the matrix becomes noise; cut the long-shots first) - **The use case in one sentence** ("primary OLTP store for a multi-tenant SaaS app, ~10k writes/sec, latency p99 < 50ms") - **Hard constraints** (e.g., "must run on-prem", "must be open source", "team has zero ops capacity for self-hosting") Ask at most 2 clarifying questions. If the user only gave you the options without a use case, ask for the use case — it determines the criteria. 2. **Pick the criteria.** Default to a balanced set across these axes (8–10 criteria is the sweet spot — fewer feels shallow, more becomes noise): | Axis | Example criteria | |---|---| | **Capability fit** | Throughput, latency, query model, consistency model, schema flexibility | | **Operational** | Self-hosted vs managed, scaling story, backup/restore, observability | | **Cost** | License, infrastructure, support, total cost of ownership at scale | | **Risk** | Vendor lock-in, ecosystem maturity, hiring market, our team's familiarity | Mention any criteria you intentionally **excluded** so the user can challenge it. ("I left out 'community size' — let me know if that matters for you.") 3. **Apply weights.** Us