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    Trade off analysis

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    Structured architectural trade-off analysis using weighted matrices and risk profiling for defensible tech decisions.

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    Trade off analysis

    Trade off analysis

    Example session with this skill installed

    We are choosing between a managed RDS Postgres instance and a self-hosted ScyllaDB cluster for a new high-throughput telemetry service. Our team has 5 backend devs and 1 DevOps engineer.

    • Read your context and instructions
    • Compiled the trade off analysis
    • Generated the UI component

    I have analyzed the trade-offs between managed RDS and self-hosted ScyllaDB based on your team size and the high-throughput requirement.

    Architecture Trade-Off Analysis

    Decision: Select a data store for a high-throughput telemetry service.

    Context: Small team (6 total) with limited DevOps bandwidth (1 FTE). High-throughput requirement suggests a need for write-scaling, but team size limits operational overhead.

    Characteristic (weight)RDS (Managed)ScyllaDB (Self-hosted)
    Elasticity (High)35
    Simplicity (High)52
    Operability (High)51
    Write Throughput (Med)35
    Cost Efficiency (Low)24

    Weighted Recommendation: RDS (Managed) scores significantly higher for your specific context. While ScyllaDB dominates in pure throughput and elasticity, the "Operability" cost is disqualifying for a team with only one DevOps engineer.

    Key Tensions:

    Throughput vs. Operability: ScyllaDB provides the required throughput but demands management effort that your 1-person DevOps team cannot sustain without neglecting other systems.

    Simplicity vs. Elasticity: RDS is easier to run but harder to scale horizontally compared to ScyllaDB’s shared-nothing architecture.

    "What Would Have to Be True":

    • For

    RDS to be the right choice: Throughput must remain within the vertical scaling limits of large AWS instances for the next 12-18 months.

    • For

    ScyllaDB to be the right choice: The team must hire 1-2 additional SREs or choose a managed ScyllaDB Cloud offering to offset the operational burden.

    Risk Profile:

    Risk TypeRDS (Managed)ScyllaDB (Self-hosted)
    TechnicalScaling ceilingComplex configuration
    OrganizationalLowHigh (Single point of failure on DevOps)
    ReversibilityMediumHigh (Complex data migration)

    Recommendation:

    RDS (Managed). Confidence:

    High. The operational risk of self-hosting a NoSQL cluster with your current headcount outweighs the performance benefits.

    ADR-Ready Summary: We will use managed RDS Postgres to minimize operational overhead. While ScyllaDB offers superior write-scaling, our current staffing (1 DevOps FTE) cannot support the maintenance of a self-hosted cluster. We will revisit this if telemetry volume exceeds the vertical limits of a db.r6g.16xlarge instance.

    Next steps

    1. Define the specific telemetry schema to confirm Postgres indexing will handle the initial load.
    2. Establish a "fitness function" to alert us when we hit 70% of maximum IOPS on the RDS instance.
    3. Evaluate ScyllaDB Cloud (managed) as a middle-ground alternative if costs allow.

    trade-off-analysis.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Evaluate competing database technologies based on team skill and scale.Decide between managed services and self-hosted infrastructure.Assess the long-term impact of adopting a new framework or language.Generate structured content for Architecture Decision Records (ADRs).

    About this skill

    Every software architecture decision your team makes follows the same broken process.

    Someone proposes microservices. Someone else argues for the monolith. A third person suggests "modular monolith" because they read a blog post last Tuesday. Three hours of whiteboarding later, the most senior person in the room wins—not because their reasoning is stronger, but because everyone is tired.

    The decision gets documented in a two-paragraph Confluence page that says "we decided to go with Option B" and nothing about why.

    This Claude skill replaces that entire process with a structured, scored, defensible architecture analysis — generated in minutes from a single paragraph describing your decision.

    Describe your architecture decision in plain English. One paragraph. That's all.

    You get back a complete analysis document that would take a senior architect a full day to produce:

    Scored Trade-off Matrix — 5–8 architecture characteristics (scalability, reliability, maintainability, security, cost, deployability) weighted to your priorities, with every option scored on a calibrated 1–5 scale. The math is visible. The reasoning is explicit. No hand-waving.

    Named Tensions — The 3 places where your stated priorities conflict with each other. The tensions most teams discover 6 months into implementation? They're surfaced before you write a single line of code.

    "What Would Have to Be True" — Borrowed from Roger Martin's strategy framework: for each option, the specific conditions that would make it the right choice. This reframes the debate from "which is best" to "which assumptions are we most confident in."

    Hidden Cost Analysis — The costs your team will miss because they don't show up on architecture diagrams: Conway's Law effects on team structure, on-call burden shifts, cognitive load increases, and migration risks that compound over quarters.

    Risk Profile — Every option scored across four dimensions: technical risk, organizational risk, timeline risk, and reversibility. Because an irreversible bad decision is categorically different from a reversible one.

    Fitness Functions — Measurable signals to monitor after the decision ships. If the decision was wrong, these are the metrics that will tell you first.

    ADR-Ready Summary — A clean Architecture Decision Record you can paste directly into your documentation. Context, decision, consequences, status — formatted and ready.

    Example

    Here's the exact prompt someone fed the skill

    "We're a fintech startup with 12 engineers. We currently have a Django monolith handling payments, user accounts, and a lending product. We're growing fast and need to decide: should we extract the payment service into a microservice, refactor into a modular monolith, or keep the monolith and optimize? We process about 50K transactions per day and expect 10x growth in the next 18 months."

    The output: 250 lines of structured analysis comparing all three options across 8 weighted characteristics. Three named tensions. Per-option risk profiles across four dimensions. A clear recommendation with confidence caveats and the conditions under which that recommendation changes. Fitness functions to track post-decision.

    The kind of document that normally takes a senior architect a full working day — produced in minutes.

    📄 The full example output is included in the download so you can judge the quality yourself.

    What is included

    SKILL.md file — 180 lines of structured architecture decision methodology. The engine behind the analysis.

    Characteristics Taxonomy — 25 architecture characteristics organized across 4 categories (operational, structural, cross-cutting, 2026-era), with 10 named tensions and selection heuristics. This is the vocabulary the skill uses to evaluate your options.

    Scoring Rubric — Anchor-based 1–5 scale with calibration examples. No more "I'd give it a 4 out of 5 for scalability" with zero justification. Every score is defensible.

    README — Step-by-step installation for Claude Code, Cursor, VS Code, and Cowork.

    Example Output — The complete fintech analysis. See exactly what to expect before you buy.

    How to install

    Upload the skill in Claude(Desktop/Web).

    Settings --> Capabilities --> Add --> Upload the .zip file

    Go back to chat

    Describe any architecture decision in plain English.

    That's it. No configuration. No coding. No API wrangling.

    Works with Claude Pro, Claude Max, or any API key.

    Who is this for

    Senior developers who are tired of architecture decisions being made by whoever talks loudest in the room.

    Software architects who want their trade-off analysis to be structured, quantified, and defensible — not a vibes-based whiteboard sketch that gets erased on Monday.

    Engineering leads evaluating technology choices who need to communicate the why behind decisions to stakeholders who weren't in the room.

    Anyone who has spent 3 hours in a meeting debating microservices vs. monolith and walked out without a clear framework for why the team chose what it chose.

    Part of Architect OS (coming soon)

    This is 1 of 45 AI-powered skills in the upcoming Architect OS — a complete operating system for software architects.

    The full OS includes

    • 45 skills across decisions, design, communication, analysis, governance, leadership, and strategy

    • 8 sub-agents for cross-functional architecture review

    • 9 frameworks wired directly into workflows

    • A context library that calibrates every output to your company, your stack, and your constraints

    Buy this skill now. When Architect OS launches, you'll already have the most important piece.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
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      Unzip into your skills folder

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