cluster-analysis
Skill2 starsChanged 6 months agoApache-2.0View on GitHub
Identify natural opinion clusters from collected judgments and characterize each cluster.
1 other project uses a version of this.
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- hu669293657/skillstheir own version, first seen Oct 31, 2026
Other versions1 project uses a version of this.
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- hu669293657/skills★ 2same name
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In this repository119 other files it gives its agents.
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- disagreement-mappingSkill
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- diversity-maximizationSkill
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- dynamic-trackingSkill
- efficient-explorationSkill
- feasibility-assessmentSkill
- feasibility-synthesisSkill
- feedback-distributionSkill
- full-rankingSkill
- futures-calibrationSkill
- gate-criteria-definitionSkill
- gate-judgmentSkill
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- The first 60 shown.
The file
Files
Cluster Analysis
Identify natural groupings of similar positions within the collected judgments. Characterize each cluster by its central position, shared reasoning patterns, and distinguishing features.
Execution
Spawn a subagent that analyzes the judgments for similarity patterns, groups them into coherent clusters, and provides characterization of each cluster.
Why Subagent
- Clustering requires holistic analysis of all judgments simultaneously
- Characterization is a bounded analytical task
- Output structure is standardized
HARD-GATE
Output MUST contain: at least 2 clusters (if genuine disagreement exists), each with cluster_id, position_summary, member_count, and characterization. If all judgments agree, output 1 cluster with a note.
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