using-serena-for-exploration
A guide for exploring codebases via Serena MCP, focusing on symbolic discovery to minimize token consumption.
Install
mkdir -p .claude/skills/using-serena-for-exploration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/304" && unzip -o skill.zip -d .claude/skills/using-serena-for-exploration && rm skill.zipInstalls to .claude/skills/using-serena-for-exploration
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.
Use when exploring codebases with Serena MCP tools for architectural understanding and pattern discovery - guides efficient symbolic exploration workflow minimizing token usage through targeted symbol reads, overview tools, and progressive narrowingKey capabilities
- →List directory structures and find specific files
- →Generate symbolic overviews of code files
- →Perform targeted symbol reading with depth control
- →Search for code patterns using regex
- →Identify referencing symbols for dependency analysis
How it works
The skill uses MCP tools to extract symbolic information like classes and functions, allowing exploration without reading entire file contents.
Inputs & outputs
When to use using-serena-for-exploration
- →Identifying project structure and architecture
- →Locating specific class or method definitions
- →Understanding code dependencies without reading full file content
About this skill
Using Serena for Exploration
Use this skill when exploring codebases with Serena MCP tools for architectural understanding and pattern discovery.
Core Principles
- Start broad, narrow progressively
- Use symbolic tools before reading full files
- Always provide file:line references
- Minimize token usage through targeted reads
Workflow
1. Initial Discovery
Use list_dir and find_file to understand project structure:
# Get repository overview
list_dir(relative_path=".", recursive=false)
# Find specific file types
find_file(file_mask="*auth*.py", relative_path="src")
2. Symbol Overview
Use get_symbols_overview before reading full files:
# Get top-level symbols in a file
get_symbols_overview(relative_path="src/auth/handler.py")
Returns classes, functions, imports - understand structure without reading bodies.
3. Targeted Symbol Reading
Use find_symbol for specific code:
# Read a specific class without body
find_symbol(
name_path_pattern="AuthHandler",
relative_path="src/auth/handler.py",
include_body=false,
depth=1 # Include methods list
)
# Read specific method with body
find_symbol(
name_path_pattern="AuthHandler/login",
relative_path="src/auth/handler.py",
include_body=true
)
Name path patterns:
- Simple name:
"login"- matches any symbol named "login" - Relative path:
"AuthHandler/login"- matches method in class - Absolute path:
"/AuthHandler/login"- exact match within file - With index:
"AuthHandler/login[0]"- specific overload
4. Pattern Searching
Use search_for_pattern when you don't know symbol names:
# Find all JWT usage
search_for_pattern(
substring_pattern="jwt\\.encode",
relative_path="src",
restrict_search_to_code_files=true,
context_lines_before=2,
context_lines_after=2,
output_mode="content"
)
Pattern matching:
- Uses regex with DOTALL flag (. matches newlines)
- Non-greedy quantifiers preferred:
.*?not.* - Escape special chars:
\\{\\}for literal braces
5. Relationship Discovery
Use find_referencing_symbols to understand dependencies:
# Who calls this function?
find_referencing_symbols(
name_path="authenticate_user",
relative_path="src/auth/handler.py"
)
Returns code snippets around references with symbolic info.
Reporting Format
Always structure findings as:
## Codebase Findings
### Current Architecture
- **Authentication:** `src/auth/handler.py:45-120`
- JWT-based auth with refresh tokens
- Session storage in Redis
### Similar Implementations
- **User management:** `src/users/controller.py:200-250`
- Uses similar validation pattern
- Can reuse `validate_credentials()` helper
### Integration Points
- **Middleware:** `src/middleware/auth.py:30`
- Hook new auth method here
- Follows pattern: check → validate → attach user
Anti-Patterns
❌ Don't: Read entire files before understanding structure
✅ Do: Use get_symbols_overview first
❌ Don't: Use full file reads for symbol searches
✅ Do: Use find_symbol with targeted name paths
❌ Don't: Search without context limits
✅ Do: Use relative_path to restrict search scope
❌ Don't: Return findings without file:line references
✅ Do: Always include exact locations: file.py:123-145
Token Efficiency
- Overview tools use ~500 tokens vs. ~5000 for full file
- Targeted symbol reads use ~200 tokens per symbol
- Pattern search with
head_limit=20caps results - Use
depth=0if you don't need child symbols
Example Session
# 1. Find auth-related files
files = find_file(file_mask="*auth*.py", relative_path="src")
# → Found: src/auth/handler.py, src/auth/middleware.py
# 2. Get overview of main handler
overview = get_symbols_overview(relative_path="src/auth/handler.py")
# → Classes: AuthHandler
# → Functions: authenticate_user, validate_token
# 3. Read specific method
method = find_symbol(
name_path_pattern="AuthHandler/authenticate_user",
relative_path="src/auth/handler.py",
include_body=true
)
# → Got full implementation of authenticate_user
# 4. Find who calls this
refs = find_referencing_symbols(
name_path="authenticate_user",
relative_path="src/auth/handler.py"
)
# → Called from: middleware.py:67, api/routes.py:123
When not to use it
- →When reading small files where full content is needed immediately
Limitations
- →Regex pattern matching is sensitive to special character escaping
- →Requires precise name path patterns for targeted symbol reads
How it compares
It uses symbolic exploration to minimize token usage compared to reading full files or using broad grep searches.
Compared to similar skills
using-serena-for-exploration side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| using-serena-for-exploration (this skill) | 9 | 8mo | Review | Intermediate |
| cursor-explorer-mcp | 6 | 8mo | No flags | Intermediate |
| react-expert | 8 | 6mo | Review | Advanced |
| analyzing-projects | 3 | 5mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
cursor-explorer-mcp
sepiabrown
Use for token-expensive operations requiring multi-file analysis - codebase exploration, broad searches, architecture understanding, tracing flows, finding implementations across files. Uses MCP cursor-agent server (company pays) with clean async interface. Do NOT use for single-file analysis, explaining code already in immediate context, or pure reasoning tasks.
react-expert
reactjs
Use when researching React APIs or concepts for documentation. Use when you need authoritative usage examples, caveats, warnings, or errors for a React feature.
analyzing-projects
CloudAI-X
Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?"
leann-search
parcadei
Semantic search across codebase using LEANN vector index
cartographer
kingbootoshi
Maps and documents codebases of any size by orchestrating parallel subagents. Creates docs/CODEBASE_MAP.md with architecture, file purposes, dependencies, and navigation guides. Updates CLAUDE.md with a summary. Use when user says "map this codebase", "cartographer", "/cartographer", "create codebase map", "document the architecture", "understand this codebase", or when onboarding to a new project. Automatically detects if map exists and updates only changed sections.
consult-zai
centminmod
Compare z.ai GLM 4.7 and code-searcher responses for comprehensive dual-AI code analysis. Use when you need multiple AI perspectives on code questions.