Locate symbol definitions and references across multi-language codebases via LSP-backed indexing.
npx skills add https://github.com/swat9013/dotfiles --skill serena-swat9013
Please help me install this Agent Skill. Skill: serena Source: https://github.com/swat9013/dotfiles/tree/main/.claude-global/skills/serena Command: npx skills add https://github.com/swat9013/dotfiles --skill serena-swat9013
Serena provides semantic, symbol-level code discovery and safe, precise symbol editing across large, multi-language repositories so developers and LLMs can reason about definitions, references, and impact before making changes.
Find the definition of the target symbol, list all referencing locations, and report whether it is safe to replace or delete the symbol.
High-intent search queries and answers about installing and using this skill.
Semantic symbol search finds symbol definitions by name and kind across large, multi-language repositories by using MCP/LSP-backed symbol indexing to map call graphs and dependency chains. It retrieves file outlines and lists symbols to help you understand code structure.
Precise symbol editing allows you to insert, replace, or delete entire symbols atomically for safe code refactoring. This enables targeted updates without line-level guesswork and coordinates safe refactors across multiple call sites.
Impact analysis locates all referencing symbols to map call graphs and dependency chains before edits or deletions. By finding definitions and tracing references via semantic search, it reports whether a symbol is safe to replace or delete.
Yes, semantic code search operates via MCP and LSP-backed symbol indexing to support multi-language repositories. It applies to tasks like finding definitions, tracing references, and coordinating safe refactors across diverse codebases.
The best way to trace call graphs is using reference and impact analysis to locate all referencing symbols. This maps dependency chains before edits, allowing you to update implementations and apply coordinated call-site fixes with minimal risk.
Use symbol-level code discovery when you need to reason about definitions, references, and impact before making changes in large repositories. Unlike text search, it understands code structure semantically to retrieve file outlines and find symbols by kind.
elophantoIndexes LSP data from multiple languages into a unified semantic graph.
MadAppGangTrace AST call chains to locate root causes of code defects.
briiirussellAudit project dependencies and lockfiles for known CVEs and supply-chain risks.
tao3kSearch code repositories by structure, semantics, or exact text.
