analogy-mapper
Skill for identifying and mapping analogies across domains
npx skills add a5c-ai/babysitter --skill analogy-mapper --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.
# 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
- Purpose
- Capabilities
- Usage Guidelines
- Process Integration
- Configuration
- Output Artifacts
What does the analogy-mapper skill do?
Skill for identifying and mapping analogies across domains
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill analogy-mapper --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.