k-kolomeitsev/data-structure-protocol
Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors
This helps developers who use AI coding agents to work more efficiently on large codebases. Instead of your AI agent re-reading the entire project every time you start a new task, DSP provides a persistent, graph-based map of your code's structure. This allows the agent to quickly understand the codebase and pick up exactly where it left off, saving time and computational resources.
Use this if you are a developer using AI coding agents (like Claude Code, Cursor, or Codex) and find your agent repeatedly scanning your codebase to understand its structure, or you need better impact analysis before refactoring.
Not ideal if you are working on very small, short-lived projects where the overhead of maintaining a code graph might outweigh the benefits.
Stars
20
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 20, 2026
Commits (30d)
0
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