Locate code definitions and references via semantic search and AST-aware queries.
npx skills add https://github.com/dzackgarza/ai --skill probe-dzackgarza
Please help me install this Agent Skill. Skill: probe Source: https://github.com/dzackgarza/ai/tree/main/opencode/skills/probe Command: npx skills add https://github.com/dzackgarza/ai --skill probe-dzackgarza
Semantic navigation and discovery across large codebases without relying on grep, enabling AST-aware extraction and structural queries.
Ask the AI to perform a semantic search across the codebase for a symbol and return its definition and usage.
High-intent search queries and answers about installing and using this skill.
You can locate function definitions and call sites using semantic search and AST-aware symbol extraction, which identifies where symbols are defined and referenced across repositories without relying on grep.
AST-aware structural query analyzes the abstract syntax tree of code to extract symbols and identify architectural patterns, enabling precise code discovery workflows and faster semantic navigation across large codebases.
You can perform a semantic search by asking the AI to locate relevant code paths and definitions across your repository, extracting function definitions and usage to understand code flow quickly.
Yes, semantic code discovery and AST-aware extraction support identifying functions, symbols, and architectural patterns within Python or other languages across large codebases.
Yes, npx usage with @probelabs/probe is required to execute semantic searches, symbol extractions, and structural queries for precise code discovery workflows.
The best way is using AST-aware structural queries and semantic search to extract symbols and locate definitions, enabling you to map architectural patterns and understand code flow across large repositories.
alangebTransform codebases into persistent knowledge graphs via AST extraction.
rakhnianskii9Trace symbol definitions and usages to map execution paths across a codebase.
ThiagoVitaleArchive completed milestones and update project documentation for the next version.
FatBySearch codebases by text, symbols, files, and natural language queries.
