Core Paradigms
- Graphify (AST-Based): Parses code into Abstract Syntax Trees. It maps exact imports, exports, and function calls to determine execution paths.
- Git-Nexus (History-Based): Analyzes Git metadata to find "logical coupling"—assuming files frequently committed together logically belong together, regardless of programmatic imports.
Token Efficiency Comparison
Graphify provides surgical precision by eliminating non-executable code, resulting in the lowest token overhead. Git-Nexus provides broader contextual clusters based on commit history.
| Traversal Method | Average Tokens Consumed | Context Description |
|---|---|---|
| Baseline Raw File Injection | ~45,000 | Massive noise, hits token limits rapidly. |
| Git-Nexus Metadata Graph | ~18,500 | Medium payload, captures historical/logical links. |
| Graphify AST Summary | ~8,200 | Leanest payload, strictly execution-path relevant. |
(Data reflects the average token payload sent to Claude for resolving a standard 3-layer deep dependency chain.)
Feature & Capability Analysis
Graphify
Graphify creates a precise, deterministic map of the codebase. It knows exactly which file imports which function.
Advantages:
- Surgical Context: Provides exact type definitions and signatures, drastically reducing LLM hallucinations.
- Zero Dead Code: Traversal follows explicit execution paths; unused or unimported files are automatically excluded.
- Language Aware: Natively understands object-oriented inheritance, interfaces, and implementations.
Context Payload Composition:
- Function Signatures & Types: 55%
- Import/Export Declarations: 30%
- Class Structures: 15%
Git-Nexus
Git-Nexus bypasses code parsing entirely, analyzing commit history to find coupled files and authorship.
Advantages:
- Cross-Language Mapping: Easily links disparate stack components (e.g., linking a Python backend change to a React frontend change if committed together).
- Configuration Context: Captures critical changes to non-code files like
.env, YAML, or Dockerfiles that AST parsers ignore. - Domain Knowledge: Identifies the primary authors/experts of specific code regions based on commit history.
Context Payload Composition:
- Commit Message Summaries: 45%
- Coupled File Paths: 40%
- Author/Ownership Metadata: 15%
Senior Dev's Take
Choosing the right tool depends entirely on the objective of the LLM prompt:
Use Graphify for: Standard coding tasks, deep refactoring, and strict type-checking tasks where execution flow and low token consumption are paramount.
Use Git-Nexus for: Architectural overviews, discovering undocumented microservice relationships, full-stack feature planning, and navigating messy legacy systems where structural imports are broken but commit patterns remain clear.