Examples
See It In
Action
From scanning your codebase to querying it through your AI agent. Copy, paste, and run.
Scan a Codebase
Build the knowledge graph. Fast structural scan — no model loaded.
bash
# Fast structural scan (FTS5 search ready in seconds)
devscriptor scan ./my-project
# Only Python files, exclude tests
devscriptor scan ./my-project -i py -e tests/,*_test.py
# Re-scan only changed files
devscriptor scan ./my-project --incremental
# Scan + embed inline (needs ~4 GB free RAM)
devscriptor scan ./my-project --embedEmbed & Search
Add semantic search, then query by keyword or meaning.
bash
# Generate vectors once (idempotent, model unloads after)
devscriptor embed
# Keyword / symbol search
devscriptor search "getUserById"
devscriptor search "connection pool" -t fulltext
# Semantic similarity search (requires embed)
devscriptor find-similar "database connection pooling"Analyze & Inspect
Static analysis, call graphs, and a health check.
bash
# Dead-code and full analysis
devscriptor analyze ./my-project -k dead-code
devscriptor analyze ./my-project -k all -o json
# Call graph from an entry point (Mermaid output)
devscriptor call-graph --entity main --format mermaid --max-depth 3
# Database stats and health check
devscriptor status
devscriptor doctor