serena
Provides semantic code understanding, symbol tracking, and precise edits using LSP.
Install
mkdir -p .claude/skills/serena && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1809" && unzip -o skill.zip -d .claude/skills/serena && rm skill.zipInstalls to .claude/skills/serena
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
This skill provides symbol-level code understanding and navigation using Language Server Protocol (LSP). Enables IDE-like capabilities for finding symbols, tracking references, and making precise code edits at the symbol level.Key capabilities
- →Queries language server for symbol definitions
- →Performs cross-file reference tracking
- →Executes semantic-aware refactoring
- →Locates symbol occurrences in large codebases
- →Validates symbol scope and relationships
How it works
Interrogates the language server to understand symbol hierarchy, scope, and memory references.
Inputs & outputs
When to use serena
- →Find symbol definitions
- →Track variable references
- →Rename symbols across files
- →Insert code at specific symbol locations
About this skill
Serena: Symbol-Level Code Understanding
Navigate and manipulate code at the symbol level using IDE-like semantic analysis powered by Language Server Protocol (LSP).
How You Can Access Serena
You may have Serena available in one or both of these ways:
Option 1: Direct MCP Tools (if configured by your orchestrator) Check your available tools for:
find_symbol,find_referencing_symbols- Symbol lookuprename_symbol,replace_symbol_body- Refactoringinsert_after_symbol,insert_before_symbol- Precise insertionsonboarding,activate_project- Project understandingwrite_memory,read_memory- Save context- And 25+ more LSP-powered tools
If you see these tools, use them directly - they provide full Serena capabilities!
Option 2: CLI Commands (always available via execute_command) You can run serena commands using:
execute_command("uvx --from git+https://github.com/oraios/serena serena <command>")
This skill focuses on CLI usage patterns. If you have direct MCP tools, prefer those for better integration.
Purpose
The serena skill provides access to Serena, a coding agent toolkit that transforms text-based LLMs into symbol-aware code agents. Unlike traditional text search (ripgrep) or structural search (ast-grep), Serena understands code semantics through LSP integration.
Key capabilities:
- Symbol Discovery: Find classes, functions, variables, and types by name across 30+ languages
- Reference Tracking: Discover all locations where a symbol is referenced or used
- Precise Editing: Insert code at specific symbol locations with surgical precision
Serena operates at the symbol level rather than the text or syntax level, providing true IDE-like understanding of code structure, scope, and relationships.
When to Use This Skill
Use the serena skill when you need symbol-level code understanding:
Code Navigation:
- Finding where a class, function, or variable is defined
- Discovering all places where a symbol is used (call sites, imports, references)
- Understanding code dependencies and relationships
- Tracing execution flow through function calls
Code Understanding:
- Analyzing impact of changes to a function or class
- Understanding inheritance hierarchies and type relationships
- Identifying dead code (symbols never referenced)
- Mapping API usage patterns across a codebase
Code Refactoring:
- Renaming symbols while tracking all usage locations
- Adding methods or fields to specific classes
- Inserting error handling after specific function calls
- Modifying all call sites of a deprecated function
Choose serena over file-search (ripgrep/ast-grep) when:
- You need to understand symbol semantics (not just text patterns)
- You want to track references across files and modules
- You need precise insertion points based on code structure
- You're working with complex, multi-file codebases
Still use file-search when:
- Searching for text patterns, comments, or strings
- Finding todos, security issues, or documentation
- You need faster, simpler pattern matching
- Symbol-level precision isn't required
Language Support
Serena uses LSP servers for semantic analysis. Most common languages are supported out-of-the-box:
- Python (pyright, jedi)
- JavaScript/TypeScript (typescript-language-server)
- Rust (rust-analyzer)
- Go (gopls)
- Java (jdtls)
- C/C++ (clangd)
- C#, Ruby, PHP, Kotlin, Swift, Scala, and 15+ more
The LSP servers provide symbol information for the language you're working with.
Core Operations
1. Finding Symbols (find_symbol)
Locate where a symbol is defined in your codebase.
Note: All examples below use the short form serena <command>. The full command is:
uvx --from git+https://github.com/oraios/serena serena <command>
# Find a class definition
execute_command("uvx --from git+https://github.com/oraios/serena serena find_symbol --name 'UserService' --type class")
# Find a function definition
execute_command("uvx --from git+https://github.com/oraios/serena serena find_symbol --name 'authenticate' --type function")
# Find a variable definition
execute_command("uvx --from git+https://github.com/oraios/serena serena find_symbol --name 'API_KEY' --type variable")
Use cases:
- Locating the definition of a class before modifying it
- Finding where a function is implemented
- Understanding where constants are defined
- Tracing type definitions in typed languages
Output format:
File: src/services/user_service.py
Line: 42
Symbol: UserService (class)
Context: class UserService(BaseService):
2. Finding References (find_referencing_symbols)
Discover all locations where a symbol is used, imported, or referenced.
# Find all usages of a class
execute_command("serena find_referencing_symbols --name 'UserService'")
# Find all call sites of a function
execute_command("serena find_referencing_symbols --name 'authenticate'")
# Find all reads/writes of a variable
execute_command("serena find_referencing_symbols --name 'API_KEY'")
Use cases:
- Impact analysis before refactoring
- Finding all call sites of a function
- Tracking API usage across modules
- Identifying unused symbols (zero references)
- Understanding data flow and dependencies
Output format:
Found 12 references to 'authenticate':
1. src/api/routes.py:34
authenticate(user_credentials)
2. src/middleware/auth.py:18
from services import authenticate
3. tests/test_auth.py:56
mock_authenticate = Mock(spec=authenticate)
...
3. Precise Code Insertion (insert_after_symbol)
Insert code at specific symbol locations with surgical precision.
# Add a method to a class
execute_command("""serena insert_after_symbol --name 'UserService' --type class --code '
def get_user_by_email(self, email: str) -> Optional[User]:
return self.db.query(User).filter_by(email=email).first()
'""")
# Insert error handling after a function call
execute_command("""serena insert_after_symbol --name 'database_query' --code '
if result is None:
raise DatabaseError("Query returned no results")
'""")
# Add a field to a dataclass
execute_command("""serena insert_after_symbol --name 'User' --type class --code '
email_verified: bool = False
'""")
Use cases:
- Adding methods to existing classes
- Inserting validation or error handling
- Adding fields to data structures
- Injecting logging or monitoring code
- Implementing missing functionality
Safety features:
- Respects indentation and code formatting
- Maintains syntactic validity
- Positions code correctly within scope
- Preserves existing code structure
Workflow Patterns
Pattern 1: Safe Refactoring
When changing a function signature or behavior:
# Step 1: Find the function definition
serena find_symbol --name 'process_payment' --type function
# Step 2: Find all call sites
serena find_referencing_symbols --name 'process_payment'
# Step 3: Analyze impact (review output)
# [Review all usage locations to understand impact]
# Step 4: Make changes with confidence
# [Update function and all call sites based on findings]
Pattern 2: Adding Functionality
When extending a class with new methods:
# Step 1: Locate the class
serena find_symbol --name 'PaymentProcessor' --type class
# Step 2: Verify no conflicts
serena find_symbol --name 'process_refund' --type function
# Step 3: Insert new method
serena insert_after_symbol --name 'PaymentProcessor' --type class --code '
def process_refund(self, payment_id: str, amount: float) -> bool:
# Implementation here
pass
'
Pattern 3: Understanding Dependencies
When analyzing code relationships:
# Step 1: Find class definition
serena find_symbol --name 'DatabaseManager' --type class
# Step 2: Find all usages
serena find_referencing_symbols --name 'DatabaseManager'
# Step 3: For each usage, find what symbols use that code
# [Repeat reference tracking to build dependency graph]
Pattern 4: Dead Code Detection
When identifying unused code:
# Step 1: Find symbol definition
serena find_symbol --name 'legacy_auth_handler'
# Step 2: Check references
serena find_referencing_symbols --name 'legacy_auth_handler'
# Step 3: If zero references (except definition), mark for removal
# [If output shows only the definition, symbol is unused]
Integration with file-search
Serena and file-search (ripgrep/ast-grep) are complementary tools. Use them together:
When to Combine Tools
Use ripgrep THEN serena:
# 1. Find potential matches with ripgrep (fast, broad)
rg "authenticate" --type py
# 2. Narrow to specific symbol with serena (precise)
serena find_symbol --name 'authenticate' --type function
serena find_referencing_symbols --name 'authenticate'
Use serena THEN ripgrep:
# 1. Find symbol definition with serena
serena find_symbol --name 'UserService'
# 2. Search for related patterns with ripgrep
rg "UserService\(" --type py # Find direct instantiations
rg "class.*UserService" --type py # Find subclasses
Complementary Strengths
| Task | Best Tool | Why |
|---|---|---|
| Find string literals | ripgrep | Text-based, fast |
| Find TODOs/comments | ripgrep | Text-based |
| Find symbol definition | serena | Symbol-aware |
| Find all references | serena | Semantic understanding |
| Find code patterns | ast-grep | Syntax-aware |
| Insert at symbol | serena | Precise positioning |
| Search across languages | ripgrep | Language-agnostic |
| Understand scope | serena | LSP semantic info |
Best Practices
1. Start with Symbol Discovery
Always locate the symbol definition first:
# GOOD: Find definition, then references
serena find_symbol --name 'MyClass'
serena find_referencing_symbols --name 'MyClass'
# AVOID: Searching for references without confirming definition exists
---
*Content truncated.*
When not to use it
- →Small projects where grep is sufficient
- →Languages without LSP support
- →Non-code files or plain text documents
Prerequisites
Limitations
- →Depends on LSP implementation quality
- →May be slow on massive repositories
- →Cannot understand dynamic, un-typed code well
How it compares
It uses semantic understanding of the AST rather than string-matching.
Compared to similar skills
serena side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| serena (this skill) | 15 | 9mo | Review | Advanced |
| dead-code | 1 | 7mo | Review | Intermediate |
| agent-analyze-code-quality | 1 | 6mo | No flags | Intermediate |
| code-refactoring-tech-debt | 1 | 4mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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