topsis-ranker
TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) ranking skill for multi-criteria evaluation
Profile →npx skills add a5c-ai/babysitter --skill topsis-ranker --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# TOPSIS Ranker ## Overview The TOPSIS Ranker skill implements the Technique for Order of Preference by Similarity to Ideal Solution methodology for multi-criteria decision analysis. It ranks alternatives based on their geometric distance from ideal and anti-ideal solutions, providing intuitive and mathematically sound rankings. ## Capabilities - Decision matrix normalization (vector, linear, max-min) - Weighted normalized matrix calculation - Ideal and anti-ideal solution identification - Euclidean distance calculation - Relative closeness coefficient computation - Alternative ranking generation - Sensitivity analysis on weights - Visualization of results ## Used By Processes - Multi-Criteria Decision Analysis (MCDA) - Tech Stack Evaluation - Geographic Market Analysis ## Usage ### Decision Matrix Construction ```python # Define decision matrix (alternatives x criteria) decision_matrix = { "alternatives": ["Option A", "Option B", "Option C", "Option D"], "criteria": ["Cost", "Quality", "Time", "Risk"], "values": [ [100000, 85, 12, 3], # Option A [150000, 92, 8, 2], # Option B [80000, 78, 15, 4], # Option C [120000, 88, 10, 2] # Option D ], "weights": [0.3, 0.35, 0.2, 0.15], "crite
- Overview
- Capabilities
- Used By Processes
- Usage
- Decision Matrix Construction
- Normalization Methods
- TOPSIS Algorithm Steps
- Relative Closeness
- Input Schema
- Output Schema
- Best Practices
- Advantages
- Limitations
- Integration Points
What does the topsis-ranker skill do?
TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) ranking skill for multi-criteria evaluation
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill topsis-ranker --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.