Give Your AI
Superpowers Over Your Codebase

from devscriptor import Devscriptor

# Initialize Devscriptor
cg = Devscriptor()

# Analyze a codebase
result = cg.analyze_codebase("/path/to/your/codebase")
print(f"Files processed: {result['files_processed']}")
print(f"Entities found: {result['total_entities']}")

from devscriptor import Devscriptor

cg = Devscriptor()

# Find functions by semantic meaning
results = cg.find_similar(
    "function that validates user input"
)

for result in results:
    print(f"{result['name']}: {result['similarity_score']:.2f}")

from devscriptor import Devscriptor
from devscriptor.context_graph import NoteType

cg = Devscriptor()

# Add an Architectural Decision Record
result = cg.context_graph.add_note(
    title="Use PostgreSQL for Main Database",
    content="We decided to use PostgreSQL...",
    note_type=NoteType.ADR,
    tags=["database", "architecture"],
    structured_data={
        "context": "Need reliable data storage",
        "decision": "Use PostgreSQL 15",
        "consequences": "Requires migration"
    }
)
print(f"Note created: {result['note_id']}")

from devscriptor import Devscriptor

cg = Devscriptor()

# Create file description
desc = cg.context_graph.file_tracker.create_file_description(
    file_path="src/auth.py",
    purpose="Handles JWT authentication",
    key_entities=["validate_token", "AuthMiddleware"],
    dependencies=["fastapi", "jose"]
)

# Record modification after editing
mod = cg.context_graph.file_tracker.create_modification(
    file_path="src/auth.py",
    changes_summary="Added refresh token support",
    rationale="Users were being logged out too frequently"
)

# Get complete context
context = cg.context_graph.file_tracker.get_file_context("src/auth.py")
print(f"Modifications: {len(context.modifications)}")

from devscriptor import Devscriptor

cg = Devscriptor()
cg.analyze_codebase("/path/to/code")

# Find dead code
dead_code = cg.detect_dead_code()
print(f"Unused functions: {len(dead_code['functions'])}")
print(f"Unused classes: {len(dead_code['classes'])}")

# Analyze complexity
complexity = cg.analyze_complexity()
for func in complexity['high_complexity']:
    print(f"{func.name}: cyclomatic={func.cyclomatic}")

# Configure in Claude Desktop or Cline
{
  "mcpServers": {
    "devscriptor": {
      "command": "python",
      "args": ["-m", "devscriptor.mcp"]
    }
  }
}

# Then ask your AI:
# "Find all functions related to user authentication"
# "What's the complexity of the payment module?"
# "Show me dead code in the codebase"