From technical-decision-making
Use weighted criteria matrices to systematically compare options and make defensible technical decisions. Use when evaluating competing approaches or vendors.
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/technical-decision-making:decision-matrixThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Build scoring matrices that make tradeoffs visible and defensible, replacing gut-feel decisions with systematic analysis.
Build scoring matrices that make tradeoffs visible and defensible, replacing gut-feel decisions with systematic analysis.
You are a senior tech lead making a decision for $ARGUMENTS using multiple competing options. Decision matrices force clarity on criteria, prevent bike-shedding, and create accountability.
List options: Clearly name each option competing. Example: "Use Postgres" vs "Use DynamoDB" vs "Use MongoDB". Make sure these are truly alternative choices, not variations of same choice.
Define criteria: List 6-10 weighted factors. Example: performance (40%), cost (25%), team capability (20%), vendor lock-in risk (10%), time-to-delivery (5%). Weights should sum to 100. Make criteria mutually exclusive (not "performance and speed" which overlap).
Score each option: On each criterion, score option A, B, C on 0-10 scale. Document your reasoning. "Performance (Postgres 8/10 due to proven scalability for our scale, DynamoDB 7/10 due to operational unknowns, MongoDB 6/10 due to memory overhead)."
Calculate weighted score: Score × weight for each criterion, sum across all criteria per option. Option with highest score wins. Example: Postgres 8.2/10 weighted score, DynamoDB 7.1, MongoDB 6.5.
Document tradeoffs: "Postgres wins decisively. Closest alternative is DynamoDB with 1.1-point gap. Gap is meaningful; DynamoDB doesn't lose on any major criterion, just accumulates small losses. If vendor lock-in risk becomes critical, revisit."
npx claudepluginhub sethdford/claude-skills --plugin tech-lead-decision-makingCompares multiple alternatives against weighted criteria for transparent decision-making. Supports weighting, scoring calibration, sensitivity analysis, and group facilitation.
Runs weighted multi-criteria analysis to clarify trade-offs and score options against explicit criteria. Useful for comparing several alternatives systematically.
Builds weighted decision matrices, analyzes trade-offs, and generates ADRs for architectural, technical, and process decisions like database selection or framework choice.