Patterns and techniques for evaluating and improving AI agent outputs.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Navigate and manipulate code at the symbol level using IDE-like semantic analysis powered by Language Server Protocol (LSP).
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 contextIf 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>")
```text
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:**
1. **Symbol Discovery**: Find classes, functions, variables, and types by name across 30+ languages
2. **Reference Tracking**: Discover all locations where a symbol is referenced or used
3. **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:
```bash
uvx --from git+https://github.com/oraios/serena serena <command>
```text
```python
# 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")
```text
**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:**
```text
File: src/services/user_service.py
Line: 42
Symbol: UserService (class)
Context: class UserService(BaseService):
```text
### 2. Finding References (`find_referencing_symbols`)
Discover **all locations** where a symbol is used, imported, or referenced.
```python
# 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'")
```text
**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:**
```text
Found 12 references to 'authenticate':
1. src/api/routes.py:34
authenticate(user_credentials)
1. src/middleware/auth.py:18
from services import authenticate
1. tests/test_auth.py:56
mock_authenticate = Mock(spec=authenticate)
...
```text
### 3. Precise Code Insertion (`insert_after_symbol`)
Insert code at specific symbol locations with surgical precision.
```python
# 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
'""")
```text
**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:
```bash
# 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]
```text
### Pattern 2: Adding Functionality
When extending a class with new methods:
```bash
# 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
'
```text
### Pattern 3: Understanding Dependencies
When analyzing code relationships:
```bash
# 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]
```text
### Pattern 4: Dead Code Detection
When identifying unused code:
```bash
# 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]
```text
## 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:**
```bash
# 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'
```text
**Use serena THEN ripgrep:**
```bash
# 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
```text
### 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:
```bash
# GOOD: Find definition, then references
serena find_symbol --name 'MyClass'
serena find_referencing_symbols --name 'MyClass'
# AVOID: Searching for references without confirming definition exists
```text
### 2. Use Specific Symbol Types
Narrow searches with `--type` when possible:
```bash
# GOOD: Specific type reduces ambiguity
serena find_symbol --name 'User' --type class
# LESS PRECISE: May match User function, User variable, etc.
serena find_symbol --name 'User'
```text
### 3. Verify Before Inserting
Always find the symbol before inserting code:
```bash
# GOOD: Verify target exists first
serena find_symbol --name 'PaymentService' --type class
# [Review output to confirm correct class]
serena insert_after_symbol --name 'PaymentService' --code '...'
# RISKY: Inserting without verification
serena insert_after_symbol --name 'PaymentService' --code '...'
```text
### 4. Review Reference Counts
Check reference output for impact analysis:
```bash
# Find references and assess impact
serena find_referencing_symbols --name 'deprecated_function'
# If 50+ references, plan careful migration
# If 0 references, safe to remove
```text
### 5. Combine with git diff
After insertions, verify changes:
```bash
serena insert_after_symbol --name 'MyClass' --code '...'
git diff # Review actual changes before committing
```text
## Supported Languages
Serena supports 30+ languages through LSP integration:
**Tier 1 (Fully tested):**
- Python, JavaScript, TypeScript, Rust, Go, Java, C/C++
**Tier 2 (Community tested):**
- C#, Ruby, PHP, Kotlin, Swift, Scala
**Tier 3 (Experimental):**
- Haskell, Elixir, Clojure, Erlang, Julia, R, and more
For the complete list and setup instructions, see
[Serena language support docs](https://oraios.github.io/serena/languages).
## Limitations
### When NOT to Use Serena
1. **Searching text/comments**: Use ripgrep instead
```bash
# WRONG TOOL: Serena doesn't search comments
serena find_symbol --name "TODO"
# RIGHT TOOL: Use ripgrep for text
rg "TODO"
Generated code: LSP may not index auto-generated files
Very large codebases: Symbol indexing can be slow
Dynamic languages without types: Limited semantic info
Serena is designed for token-efficient code navigation:
# Traditional approach (inefficient)
execute_command("cat entire_file.py") # 1000+ tokens
# [Search for symbol manually in output]
# Serena approach (efficient)
serena find_symbol --name 'MyClass' # 50 tokens
# [Get precise location immediately]
```text
### Speed Characteristics
- **Symbol lookup**: Near-instant (LSP indexed)
- **Reference finding**: Fast (O(log n) with indexing)
- **Code insertion**: Instant (direct file modification)
**Comparison with alternatives:**
- Ripgrep: Faster for text search (no semantic understanding)
- AST-grep: Comparable speed (syntax vs semantic)
- Serena: Slower initial startup (LSP indexing), faster precise queries
## Troubleshooting
### Symbol Not Found
If `find_symbol` returns no results:
1. **Verify symbol exists**: Use ripgrep to confirm
```bash
rg "class MyClass" --type py
Check language server: Ensure LSP is configured for the language
serena status # Check LSP server status
Try case variations: Symbol names are case-sensitive
serena find_symbol --name 'myclass' # Try different cases
Rebuild index: Force LSP to re-index
serena reindex # Rebuild symbol index
If find_referencing_symbols returns hundreds of results:
Use file-search first: Narrow scope with ripgrep
rg "MyClass" src/services/ # Limit to specific directory
serena find_referencing_symbols --name 'MyClass' --path src/services/
Filter by reference type: Focus on specific usage patterns
# Look for imports only
rg "from .* import.*MyClass" --type py
Prioritize recent changes: Check git history first
git log --all -p -S 'MyClass' --since="1 week ago"
If insert_after_symbol fails:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Patterns and techniques for evaluating and improving AI agent outputs.
日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
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AI-powered wiki generation for code repositories with commands, agents, and skills
日本語の概要は準備中です。原文の説明を表示しています。
Use when building .NET 10 or C# 14 applications; when using minimal APIs, modular monolith patterns, or feature folders; when implementing HTTP resilience, Options pattern, Channels, or validation; when seeing outdated patterns like old extension method syntax
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Implements accessible .NET UI. SemanticProperties, ARIA, AutomationPeer, testing per platform.
日本語の概要は準備中です。原文の説明を表示しています。