Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/getzep/graphiti/claude-mdgit clone --depth 1 https://github.com/getzep/graphitiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/getzep/graphiti/claude-md)<a href="https://agentmods.dev/instructions/getzep/graphiti/claude-md"><img src="https://agentmods.dev/badge/instructions/getzep/graphiti/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01739 | $0.01739 |
| Opus 5 | $0.00870 | $0.00870 |
| Sonnet 5 | $0.00348 | $0.00348 |
| Haiku 4.5 | $0.00174 | $0.00174 |
Grade A, and why
graphiti CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
Graphiti is a Python framework for building temporally-aware knowledge graphs designed for AI agents. It enables real-time incremental updates to knowledge graphs without batch recomputation, making it suitable for dynamic environments.
Key features:
- Bi-temporal data model with explicit tracking of event occurrence times
- Hybrid retrieval combining semantic embeddings, keyword search (BM25), and graph traversal
- Support for custom entity definitions via Pydantic models
- Integration with Neo4j and FalkorDB as graph storage backends
- Optional OpenTelemetry distributed tracing support
Development Commands
Main Development Commands (run from project root)
# Install dependencies
uv sync --extra dev
# Format code (ruff import sorting + formatting)
make format
# Lint code (ruff + pyright type checking)
make lint
# Run tests
make test
# Run all checks (format, lint, test)
make check
Server Development (run from server/ directory)
cd server/
# Install server dependencies
uv sync --extra dev
# Run server in development mode
uvicorn graph_service.main:app --reload
# Format, lint, test server code
make format
make lint
make test
MCP Server Development (run from mcp_server/ directory)
cd mcp_server/
# Install MCP server dependencies
uv sync
# Run with Docker Compose
docker-compose up
Code Architecture
Core Library (graphiti_core/)
- Main Entry Point:
graphiti.py- Contains the mainGraphiticlass that orchestrates all functionality - Graph Storage:
driver/- Database drivers for Neo4j and FalkorDB - LLM Integration:
llm_client/- Clients for OpenAI, Anthropic, Gemini, Groq - Embeddings:
embedder/- Embedding clients for various providers - Graph Elements:
nodes.py,edges.py- Core graph data structures - Search:
search/- Hybrid search implementation with configurable strategies - Prompts:
prompts/- LLM prompts for entity extraction, deduplication, summarization - Utilities:
utils/- Maintenance operations, bulk processing, datetime handling
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 182 lines · 1,739 tokens per session scan A d3847b7a3db5
graphiti CLAUDE.md is an instructions file published in the GitHub repository getzep/graphiti (30,564 stars, last pushed today), licensed Apache-2.0. It adds 1,739 tokens to every session, about $0.0087 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
Yuxi AGENTS.md
AGENTS.md instructions for xerrors/Yuxi, covering yuxi agent 开发约定, 每次任务先加载什么, 任务与决策, 不能破坏的系统事实 and 证据规则.
second-brain CLAUDE.md
Claude Code instructions for henrydaum/second-brain, covering second brain — architecture notes, ⚡ the kernel (read first), the layout (trees.py), what ships in the app's tree (bundled/) and the kernel boundary (the one rule).
Yuxi CLAUDE.md
Claude Code instructions for xerrors/Yuxi, a project described as: 可私有部署的多租户知识智能体平台：统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows.
ollama CLAUDE.md
Claude Code instructions for ollama/ollama: See AGENTS.md for the shared agent instructions for this repository.
plano CLAUDE.md
Instructions for katanemo/plano, covering claude.md, build & test commands, rust — wasm plugins (must target wasm32-wasip1), rust — brightstaff binary (native target) and rust — tests, format, lint.
autocontext CLAUDE.md
Claude Code instructions for greyhaven-ai/autocontext, covering claude.md, project overview, repository layout, commands and setup.