skill-search-optimizer

To optimize skill descriptions for semantic search, apply frontmatter structure and description patterns that emphasize tool coverage, usage contexts, and outcomes, improving relevance for broad and specific queries.

The best way to improve skill discoverability on MoltHub is to align frontmatter indexing signals with semantic search rules, rewriting descriptions to surface keywords like docker or CI/CD for multiple search intents.

Yes, you can refresh search embeddings by version bumping and republishing your skill, which tests visibility across broad and specific queries using registry tooling.

Tool-focused, pattern-focused, and workflow-focused description variants rank skills across different search intents by structuring action-oriented text that aligns with semantic indexing rules.

Your skill may not surface in specific query results because its description lacks semantic search signals, requiring frontmatter optimization and keyword emphasis to match indexing rules.

Yes, frontmatter structure directly affects how skills are indexed and previewed, ensuring the name and description surface correctly in search signals and previews.