compare

Solid

Structured comparison of 2+ alternatives with consistent criteria and decision matrix

AI & Automation 15 stars 3 forks Updated 3 days ago MIT

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Quality Score: 83/100

Stars 20%
40
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Compare Structured comparison of 2+ alternatives. Enforces a comparison matrix with consistent criteria so every alternative is evaluated on the SAME data points. ## Steps 1. **Define the comparison frame**: - List all alternatives to compare (minimum 2) - Identify the use case or decision context (WHY is this comparison needed?) - Ask the user for must-have requirements vs nice-to-have criteria 2. **Define evaluation criteria** before searching (prevents cherry-picking): - Choose 5-8 criteria relevant to the use case - Common technical criteria: performance, developer experience, ecosystem/community, documentation quality, maintenance status, license, cost, learning curve - Weight criteria: must-have vs important vs nice-to-have - Every criterion MUST be evaluated for ALL alternatives (no gaps) 3. **Research each alternative** using `search` and `extract`: - `search(action="search", query="[alternative] [criterion] benchmark OR comparison")` - For each alternative, gather the SAME data points - Prefer quantitative data (benchmarks, stars, download counts, release frequency) - Note data recency — a 2023 benchmark may not reflect 2026 reality - Use `extract` on official docs for feature verification 4. **Build the comparison matrix**: ``` | Criterion (weight) | Alternative A | Alternative B | Alternative C | |---------------------|---------------|---------------|---------------| | Performance (must) | [data+source] | [da...

Details

Author
n24q02m
Repository
n24q02m/wet-mcp
Created
5 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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