Locate code snippets, symbols, and documentation via semantic search.
npx skills add https://github.com/marcelocantos/skills --skill vera-marcelocantos
Please help me install this Agent Skill. Skill: vera Source: https://github.com/marcelocantos/skills/tree/main/skills/vera Command: npx skills add https://github.com/marcelocantos/skills --skill vera-marcelocantos
Developers often struggle to discover where specific behavior, symbols, or documentation reside in large repositories, spending excessive time parsing files or running generic grep commands.
Ask the assistant to perform a semantic search, for example say “search for authentication middleware in the repository”.
High-intent search queries and answers about installing and using this skill.
You can locate code snippets and symbols in a large repository using semantic AI search to find relevant source code and documentation instantly without manual file parsing.
Semantic code search uses AI to understand the meaning of source code and documentation, enabling automated overviews and quick onboarding of unfamiliar codebases.
Yes, semantic AI code search requires an indexed repository and the Vera CLI on PATH to locate relevant code snippets, symbols, and documentation effectively.
Yes, you can use regex-based grep limited to the indexed repository for precise pattern matching, alongside call-graph reference lookup to identify callers and callees of a given symbol for debugging.
The best way to find implementation details like authentication middleware is using semantic AI search, which understands contextual meaning to return relevant code and runtime artifacts directly.
A GPU is optional for running embedding models during repository indexing; you can use API-backed embedding models as an alternative to generate semantic search results.
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