Agent skill

Graphiti Guide

by wentorai in wentorai/research-plugins

Build real-time knowledge graphs for AI agents using Graphiti by Zep

MITAuto-check passedKnowledge Management

Install Graphiti Guide

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .claude/skills/graphiti-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .claude/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .agents/skills/graphiti-guide && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .agents/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .cursor/skills/graphiti-guide && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .cursor/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/wentorai/research-plugins.git --path skills/tools/knowledge-graph/graphiti-guide

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .gemini/skills/graphiti-guide && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .gemini/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .github/skills/graphiti-guide && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .github/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add wentorai/research-plugins --skill graphiti-guide -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins graphiti-guide --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/tools/knowledge-graph/graphiti-guide .opencode/skills/graphiti-guide && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "graphiti-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/tools/knowledge-graph/graphiti-guide into .opencode/skills/graphiti-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graphiti-guide", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: graphiti-guide
GitHub stars: 298
Used in: 1 other repo
Token cost: ~2.1k tokens
SKILL.md length: 504 words
Files: 1
Skills in repo: 405
Repo updated: Jun 19, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Build real-time knowledge graphs for AI agents using Graphiti by Zep

Tasks that involve Knowledge graphs
SKILL.md covers Overview, Installation and Setup, Core Features and Research Workflow Integration, plus 2 more sections
Calls pip and docker; needs NEO4J_PASSWORD and OPENAI_API_KEY

What it does

Graphiti Guide is an agent skill from wentorai/research-plugins. Build real-time knowledge graphs for AI agents using Graphiti by Zep

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Knowledge Management, covering Knowledge graphs. It works with Neo4j. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

Tasks that involve Knowledge graphs

Example prompts

“/graphiti-guide”

Requirements

Python 3
Docker
A credential in OPENAI_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- pip
- docker
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
- docs.getzep.com
- neo4j.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- NEO4J_PASSWORD
- OPENAI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Graphiti Guide loads about 2.1k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 504 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~21
When it runs · the whole SKILL.md, loaded when a task matches: ~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 504 words, ~2,069 tokens.

Download SKILL.mdSave it as .claude/skills/graphiti-guide/SKILL.md (or your agent's skills folder).

name: graphiti-guide
description: Build real-time knowledge graphs for AI agents using Graphiti by Zep

Graphiti Guide

Overview

Graphiti is an open-source framework for building and querying dynamic, temporally-aware knowledge graphs designed specifically for AI agent applications. Developed by Zep, Graphiti enables agents to maintain persistent, structured memory that evolves over time, capturing entities, relationships, and facts extracted from conversational and documentary sources.

Traditional knowledge graphs are static structures that require manual curation and batch updates. Graphiti takes a fundamentally different approach: it incrementally builds and updates the graph in real-time as new information arrives, resolving contradictions, merging duplicate entities, and maintaining temporal metadata that tracks when facts were established and whether they remain current.

For academic researchers, Graphiti offers a powerful framework for constructing domain-specific knowledge graphs from research literature, experimental observations, and collaborative discussions. With over 23,000 GitHub stars, the project has gained significant traction in both the AI engineering and research communities as a practical bridge between unstructured text and structured, queryable knowledge.

Installation and Setup

Install Graphiti via pip:

bash

pip install graphiti-core

Graphiti requires a Neo4j database for graph storage. Set up Neo4j using Docker:

bash

docker run -d \
  --name neo4j-graphiti \
  -p 7474:7474 -p 7687:7687 \
  -e NEO4J_AUTH=neo4j/your-password \
  -e NEO4J_PLUGINS='["apoc"]' \
  neo4j:5

Configure environment variables for your LLM provider and Neo4j connection:

bash

export NEO4J_URI=bolt://localhost:7687
export NEO4J_USER=neo4j
export NEO4J_PASSWORD=$NEO4J_PASSWORD
export OPENAI_API_KEY=$OPENAI_API_KEY

Initialize Graphiti in your Python project:

python

from graphiti_core import Graphiti

graphiti = Graphiti(
    neo4j_uri="bolt://localhost:7687",
    neo4j_user="neo4j",
    neo4j_password=$NEO4J_PASSWORD,
)

# Build indices for efficient querying
await graphiti.build_indices()

Core Features

Incremental Graph Construction: Add episodes of information that are automatically parsed into entities and relationships:

python

from graphiti_core.nodes import EpisodeType
from datetime import datetime

# Add a research observation
await graphiti.add_episode(
    name="experiment_log_2026_03_10",
    episode_body="""
    The CRISPR-Cas9 experiment targeting gene BRCA1 in HeLa cells
    showed 87% knockout efficiency. The guide RNA sequence gRNA-42
    was designed using the Benchling platform. Dr. Chen supervised
    the experiment, which used the protocol established in our
    2025 Nature Methods paper.
    """,
    source=EpisodeType.text,
    source_description="Lab notebook entry",
    reference_time=datetime(2026, 3, 10),
)

Graphiti automatically extracts entities (BRCA1, HeLa cells, Dr. Chen, gRNA-42, Benchling), establishes relationships (gRNA-42 targets BRCA1, Dr. Chen supervised the experiment), and records temporal metadata.

Temporal Awareness: Knowledge graphs built with Graphiti track when facts were established and can reason about changes over time:

python

# Add an update that modifies a previous fact
await graphiti.add_episode(
    name="experiment_update",
    episode_body="""
    After reanalysis, the CRISPR knockout efficiency for BRCA1
    in HeLa cells was revised to 82% due to off-target effects
    detected in the secondary sequencing run.
    """,
    source=EpisodeType.text,
    source_description="Updated analysis",
    reference_time=datetime(2026, 3, 12),
)

The graph updates the efficiency value while maintaining the historical record, enabling queries about both current and historical states of knowledge.

Semantic Search: Query the knowledge graph using natural language:

python

# Search for relevant entities and facts
results = await graphiti.search(
    query="What is the knockout efficiency for BRCA1?",
    num_results=5,
)

for result in results:
    print(f"Fact: {result.fact}")
    print(f"Source: {result.source_description}")
    print(f"Valid from: {result.valid_at}")
    print(f"Confidence: {result.score}")
    print("---")

Entity Resolution: Graphiti handles duplicate and variant entity references automatically. References to "CRISPR-Cas9", "CRISPR", and "Cas9 system" are resolved to the appropriate entities based on context, reducing manual curation overhead.

Show full SKILL.md (196 more words)Show less

Research Workflow Integration

Literature Knowledge Base: Build a continuously growing knowledge graph from your reading notes and paper summaries:

python

# Process a batch of paper summaries
papers = [
    {
        "title": "Attention Is All You Need",
        "summary": "Vaswani et al. introduced the Transformer architecture...",
        "date": datetime(2017, 6, 12),
    },
    {
        "title": "BERT: Pre-training of Deep Bidirectional Transformers",
        "summary": "Devlin et al. proposed BERT, a masked language model...",
        "date": datetime(2018, 10, 11),
    },
]

for paper in papers:
    await graphiti.add_episode(
        name=paper["title"],
        episode_body=paper["summary"],
        source=EpisodeType.text,
        source_description=f"Paper summary: {paper['title']}",
        reference_time=paper["date"],
    )

Then query across your entire reading history to find connections, trace the evolution of ideas, and identify foundational works.

Experimental Knowledge Management: Track the relationships between experiments, reagents, instruments, protocols, and personnel. This creates an institutional memory that survives personnel turnover and helps new lab members quickly understand the research context.

Systematic Review Support: As you read and annotate papers for a systematic review, feed summaries into Graphiti to build a structured representation of findings, methodologies, and populations studied. Query the resulting graph to identify patterns and gaps.

Agent Memory for Research Assistants: Integrate Graphiti as the memory backend for AI research assistants. The agent can accumulate knowledge from each interaction and provide increasingly informed responses:

python

# Research agent with persistent memory
async def research_agent_step(user_query, conversation_context):
    # Retrieve relevant knowledge
    memories = await graphiti.search(
        query=user_query,
        num_results=10,
    )

    # Include memories in the agent context
    context = format_memories(memories) + conversation_context

    # Generate response using LLM
    response = await generate_response(user_query, context)

    # Store new knowledge from the interaction
    await graphiti.add_episode(
        name=f"conversation_{datetime.now().isoformat()}",
        episode_body=f"User asked: {user_query}\nResponse: {response}",
        source=EpisodeType.message,
        source_description="Research assistant conversation",
        reference_time=datetime.now(),
    )

    return response

Graph Exploration and Maintenance

Access the Neo4j browser at http://localhost:7474 to visually explore your knowledge graph. Use Cypher queries for advanced exploration:

cypher

// Find all entities related to a specific gene
MATCH (e:Entity)-[r]-(connected)
WHERE e.name CONTAINS 'BRCA1'
RETURN e, r, connected
LIMIT 50

// Find the most connected entities (research hubs)
MATCH (e:Entity)-[r]-()
RETURN e.name, COUNT(r) AS connections
ORDER BY connections DESC
LIMIT 20

Periodically review and clean the graph to maintain quality. Remove incorrectly extracted entities and merge duplicates that automated resolution missed.

References

Graphiti repository: https://github.com/getzep/graphiti
Zep documentation: https://docs.getzep.com/
Neo4j graph database: https://neo4j.com/
Temporal knowledge graph concepts in the project documentation

Files

Just SKILL.md in skills/tools/knowledge-graph/graphiti-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

brycewang-stanford/Auto-Empirical-Research-Skillsskills/43-wentorai-research-plugins/skills/tools/knowledge-graph/graphiti-guide

Compare with similar skills

Graphiti Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Graphiti Guide compared with similar skills
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Graphiti Guide this skillwentorai/research-plugins	298	1 repos	~2.1k	Automated safety check: Pass	MIT	3 mo ago
Amazon Neptuneaws/agent-toolkit-for-aws	2.8k	—	~4.7k	Automated safety check: Pass	Apache-2.0	today
Neo4j Document Import Skillneo4j-contrib/neo4j-skills	114	—	~5.4k	Automated safety check: Notes	MIT	2 days ago
Project Orchestratorthis-rs/project-orchestrator	140	—	~2.6k	Automated safety check: Pass	Custom licence	today
Neo4j Driver Python Skillneo4j-contrib/neo4j-skills	114	—	~4.1k	Automated safety check: Notes	MIT	2 days ago
Neo4j Graphrag Skillneo4j-contrib/neo4j-skills	114	—	~4.2k	Automated safety check: Notes	MIT	2 days ago

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Questions about Graphiti Guide

What does Graphiti Guide do?

Build real-time knowledge graphs for AI agents using Graphiti by Zep. Graphiti Guide is an agent skill from wentorai/research-plugins.

When should I use Graphiti Guide?

Graphiti Guide fits situations like: tasks that involve Knowledge graphs.

How do I install Graphiti Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill graphiti-guide -a claude-code`. Or copy the skill folder (skills/tools/knowledge-graph/graphiti-guide in wentorai/research-plugins) into .claude/skills/graphiti-guide in your project. Claude Code loads it when a task matches its description.

How do I install Graphiti Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill graphiti-guide -a codex`. Or copy the skill folder (skills/tools/knowledge-graph/graphiti-guide in wentorai/research-plugins) into .agents/skills/graphiti-guide in your project. Codex loads it when a task matches its description.

Can I use Graphiti Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill graphiti-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/graphiti-guide, .gemini/skills/graphiti-guide, .github/skills/graphiti-guide and .opencode/skills/graphiti-guide in your project.

What does Graphiti Guide need to run?

Going by SKILL.md and its folder, Graphiti Guide needs the command-line tools its instructions call (pip and docker) and credentials named NEO4J_PASSWORD and OPENAI_API_KEY. Our summary lists: Python 3; Docker; A credential in OPENAI_API_KEY.

Does Graphiti Guide access the network?

SKILL.md names 3 domains. As links in the text: github.com, docs.getzep.com and neo4j.com. This is read from the text; nothing was executed.

Is Graphiti Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Graphiti Guide use?

Graphiti Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Graphiti Guide use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Graphiti Guide?

Skills that share tags, products or a category with Graphiti Guide: Amazon Neptune (aws/agent-toolkit-for-aws, 2.8k stars), Neo4j Document Import Skill (neo4j-contrib/neo4j-skills, 114 stars), Project Orchestrator (this-rs/project-orchestrator, 140 stars) and Neo4j Driver Python Skill (neo4j-contrib/neo4j-skills, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Graphiti Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Graphiti Guide

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Graphiti Guide

Overview

Installation and Setup

Core Features

Research Workflow Integration

Graph Exploration and Maintenance

References

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from wentorai/research-plugins

Related

Questions about Graphiti Guide