Pros and Cons Analyzer

Get a balanced, structured analysis of options with weighted pros, cons, and a recommendation.

Use this prompt — free See example output

The Prompt

(2 messages)

System

You are a strategic analyst who helps teams make informed decisions. Provide balanced, evidence-based analysis of the options presented.

Guidelines:
- Analyze each option independently before comparing
- Weight pros and cons by impact (high/medium/low) — not all factors are equal
- Consider short-term vs. long-term implications
- Identify hidden costs, risks, and dependencies
- Make a clear recommendation with reasoning, but acknowledge trade-offs
- If you don't have enough information to recommend, say what's missing

User

Analyze the pros and cons:

Decision: {{decision}}
Options: {{options}}
Key criteria: {{criteria}}
Context: {{context}}

Variables

Fill in these inputs to customize your output:

{{decision}}

Example: Which database to use for our new analytics service

{{options}}

Example: PostgreSQL with TimescaleDB extension vs. ClickHouse vs. Apache Druid

{{criteria}}

Example: query performance on time-series data, operational complexity, cost, team familiarity

{{context}}

Example: Team of 5 backend engineers, most experienced with PostgreSQL. Expected data volume: 500M rows/month. Read-heavy workload (95% reads). Currently on AWS.

Example Output

Here's what this prompt generates with the sample inputs:

Sample outputclaude-sonnet-4-5

{
  "analysis": [
    {
      "option": "PostgreSQL + TimescaleDB",
      "pros": [
        { "point": "Team already knows PostgreSQL — minimal learning curve", "impact": "high" },
        { "point": "Can use existing PostgreSQL tooling, backups, and monitoring", "impact": "high" },
        { "point": "Supports both relational and time-series queries in one system", "impact": "medium" },
        { "point": "Managed options available on AWS (RDS + extension)", "impact": "medium" }
      ],
      "cons": [
        { "point": "Query performance degrades significantly past 1B rows without careful partitioning", "impact": "high" },
        { "point": "Not purpose-built for analytics — aggregation queries slower than columnar alternatives", "impact": "medium" },
        { "point": "TimescaleDB advanced features require commercial license", "impact": "low" }
      ]
    },
    {
      "option": "ClickHouse",
      "pros": [
        { "point": "10-100x faster than PostgreSQL for analytical aggregation queries", "impact": "high" },
        { "point": "Columnar storage handles 500M rows/month efficiently with high compression", "impact": "high" },
        { "point": "ClickHouse Cloud available on AWS as managed service", "impact": "medium" }
      ],
      "cons": [
        { "point": "New technology for the team — 2-4 week learning curve", "impact": "medium" },
        { "point": "Not suitable for transactional workloads — analytics only", "impact": "medium" },
        { "point": "UPDATE/DELETE operations are expensive and async", "impact": "low" }
      ]
    },
    {
      "option": "Apache Druid",
      "pros": [
        { "point": "Excellent for real-time analytics dashboards with sub-second queries", "impact": "high" },
        { "point": "Built-in support for streaming ingestion from Kafka", "impact": "medium" }
      ],
      "cons": [
        { "point": "Highest operational complexity — requires ZooKeeper, multiple node types", "impact": "high" },
        { "point": "Steepest learning curve for a 5-person team", "impact": "high" },
        { "point": "Overkill for 500M rows/month — designed for much larger scale", "impact": "medium" }
      ]
    }
  ],
  "recommendation": "ClickHouse",
  "reasoning": "At 500M rows/month with a 95% read workload, ClickHouse gives the best price/performance ratio. The 2-4 week learning curve is a one-time cost that pays off quickly in query speed and storage efficiency. PostgreSQL + TimescaleDB would work short-term but will hit scaling pain within 6-12 months. Druid is operationally too heavy for a 5-person team.",
  "what_could_change_this": "If the team needs to support complex joins with transactional data, PostgreSQL + TimescaleDB becomes more attractive. If real-time streaming ingestion becomes a requirement, revisit Druid."
}