Best use case
analogy-mapper is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Skill for identifying and mapping analogies across domains
Teams using analogy-mapper should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analogy-mapper/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analogy-mapper Compares
| Feature / Agent | analogy-mapper | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Skill for identifying and mapping analogies across domains
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analogy Mapper Skill ## Purpose Identify and map structural analogies across scientific domains to enable cross-domain insight transfer and creative hypothesis generation. ## Capabilities - Identify structural similarities - Map relationships across domains - Transfer insights between fields - Generate analogical hypotheses - Evaluate analogy strength - Document mappings ## Usage Guidelines 1. Define source domain 2. Identify target domain 3. Map structural elements 4. Identify correspondences 5. Generate insights 6. Evaluate validity ## Process Integration Works within scientific discovery workflows for: - Cross-domain discovery - Creative hypothesis generation - Knowledge transfer - Pattern recognition ## Configuration - Domain ontologies - Mapping algorithms - Similarity metrics - Output formatting ## Output Artifacts - Analogy mappings - Structural correspondences - Insight reports - Validity assessments
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