Search source files by natural language queries and return ranked code matches.
npx skills add https://github.com/hasparus/claude-skills-dotfiles --skill osgrep-hasparus
Please help me install this Agent Skill. Skill: osgrep Source: https://github.com/hasparus/claude-skills-dotfiles/tree/main/osgrep Command: npx skills add https://github.com/hasparus/claude-skills-dotfiles --skill osgrep-hasparus
Semantic code search uses natural language queries to locate relevant source files by intent, returning file paths with line numbers and code snippets.
Ask osgrep to locate where a concept is implemented using a natural-language query.
High-intent search queries and answers about installing and using this skill.
Semantic code search locates relevant source files by concept or behavior using natural language queries. It returns file paths, line numbers, and code snippets ranked by semantic relevance across large codebases.
Semantic code search matches natural language queries to source code by underlying concept rather than exact string matching. It surfaces file paths and line numbers to show where specific behaviors are implemented.
Yes, semantic code search supports targeted searches with optional path constraints. Applying path constraints narrows the search scope to return file paths and code snippets only within the specified directories.
Use natural language to describe the component's behavior or concept. The search matches your query to the underlying intent and returns ranked file paths with line numbers and code snippets for context.
Yes, semantic code search is designed to apply across large codebases. It ranks results by semantic relevance and returns file paths with line numbers to help you locate concepts across many source files.
Code search returns file paths with line numbers and code snippets. These results are ranked by semantic relevance to your natural language query, providing quick context for how a feature works.
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