Context Graph Use Cases

The Context Graph becomes most powerful when combined with the Meta Agent’s tool calling capabilities. This page demonstrates practical use cases where natural language queries are transformed into dynamic Cypher queries, providing deep insights into your infrastructure.

The Meta Agent has built-in tools for interacting with the Context Graph API. These tools allow it to fetch schema, scan nodes, execute Cypher queries, store relationships, and create new nodes—all through natural language conversation.

Meta Agent Context Graph Tools

The Meta Agent has access to the following Context Graph tools:

Tool	Description
Fetch Graph Schema	Retrieves the current graph schema including node types and relationships
Scan Graph Nodes	Searches for nodes matching specific criteria
Execute Cypher Query	Runs dynamic Cypher queries against the graph
Store Relationship	Creates new relationships between existing nodes
Create Node	Adds new nodes to the graph with specified labels and properties

Use Case 1: AWS IAM Permission Analysis

Understand your AWS IAM permission structure across multiple accounts by querying roles, policies, and their relationships.

Example Prompt

Show me all AWS IAM roles and their relationships with policies
in the context graph. I want to understand the permission
structure across our AWS accounts.

What Happens

The Meta Agent executes a series of tool calls:

Fetches Graph Schema - Understands available node types and relationships
Scans for IAM Nodes - Identifies AWS-related entities
Executes Dynamic Cypher Queries - Retrieves roles, policies, and their connections

Sample Generated Queries

The Meta Agent dynamically generates queries like:

MATCH (role:AWSRole)-[rel:POLICY]->(policy)
WHERE policy:AWSManagedPolicy OR policy:AWSInlinePolicy
RETURN role.name AS role_name,
       role.arn AS role_arn,
       type(rel) AS relationship,
       policy.name AS policy_name,
       labels(policy) AS policy_type
ORDER BY role.name, policy.name
LIMIT 100

Results

The Meta Agent provides:

Summary statistics - Total roles, policies, and accounts
Account breakdown - Resources organized by AWS account
Role categorization - SSO roles, service-linked roles, custom roles
Visual diagrams - Mermaid charts showing permission structures

Use Case 2: Dependency Impact Analysis

Before making infrastructure changes, understand what resources depend on a specific component.

Example Prompt

What services and resources depend on the user-auth database?
Show me the full dependency chain.

What Happens

Identifies the target resource - Finds the user-auth database node
Traces relationships - Follows DEPENDS_ON, CONNECTS_TO, and USES relationships
Builds dependency tree - Creates a comprehensive impact map

Sample Generated Query

MATCH path = (dependent)-[*1..3]->(db:Database {name: 'user-auth'})
RETURN DISTINCT labels(dependent) AS resource_type,
       dependent.name AS resource_name,
       length(path) AS dependency_depth,
       [rel in relationships(path) | type(rel)] AS relationship_chain
ORDER BY dependency_depth, resource_type

Use Case 3: Security Vulnerability Correlation

Correlate CVE data with your actual infrastructure to understand real exposure.

Example Prompt

Search the context graph for repositories with known CVEs
and show me which dependencies are affected.

What Happens

Scans for CVE-related nodes - Finds vulnerability records
Correlates with repositories - Links CVEs to affected code
Traces to dependencies - Shows which packages introduce vulnerabilities

Sample Generated Query

MATCH (repo:GitHubRepository)-[:REQUIRES]->(dep:Dependency)
WHERE dep.name IN ['jinja2', 'pyyaml', 'requests']
RETURN repo.name AS repository,
       dep.name AS dependency,
       dep.version AS version
ORDER BY repo.name

Use Case 4: Cross-Account Resource Discovery

Find all resources across multiple cloud accounts and understand their relationships.

Example Prompt

List all EC2 instances across our AWS accounts and show which
IAM roles they're using.

Sample Generated Query

MATCH (instance:EC2Instance)-[:USES_ROLE]->(role:AWSRole)
OPTIONAL MATCH (role)-[:POLICY]->(policy)
RETURN instance.id AS instance_id,
       instance.name AS instance_name,
       role.name AS role_name,
       COLLECT(policy.name) AS attached_policies,
       CASE
         WHEN instance.id CONTAINS 'i-' THEN 'Running'
         ELSE 'Unknown'
       END AS status
ORDER BY role_name

Use Case 5: Creating Custom Relationships

The Meta Agent can also create new relationships to enrich your graph.

Example Prompt

Create a relationship showing that the payments-service
depends on the user-auth database for authentication.

What Happens

Validates nodes exist - Confirms both resources are in the graph
Creates relationship - Adds DEPENDS_ON relationship with metadata
Confirms creation - Returns the new relationship details

Use Case 6: GitHub Repository Analysis

Analyze code repositories, their dependencies, and relationships.

Example Prompt

Show me all GitHub repositories and their dependency counts.
Which repos have the most external dependencies?

Sample Generated Query

MATCH (repo:GitHubRepository)
OPTIONAL MATCH (repo)-[:REQUIRES]->(dep:Dependency)
WITH repo, COUNT(dep) AS dep_count
RETURN repo.name AS repository,
       dep_count AS dependency_count
ORDER BY dep_count DESC
LIMIT 20

Best Practices

Writing Effective Prompts

Do	Don’t
Be specific about what you’re looking for	Use vague terms like “show me everything”
Mention the resource types you care about	Assume the agent knows your context
Ask for relationships explicitly	Only ask for node properties
Request summaries for large datasets	Ask for unlimited results

Example Good Prompts

“Show me all Lambda functions and their IAM execution roles in account 123456789”
“What S3 buckets are accessible from the public internet?”
“Trace the data flow from our API Gateway to the backend databases”
“Which Kubernetes deployments use secrets from AWS Secrets Manager?”

What’s Next

Meta Agent - Learn more about the Meta Agent’s full capabilities
Graph Visualization - See your infrastructure visually
Queries - Write Cypher queries directly
Data Sources - Add more data to your graph

Introduction

Quick Start

Web Interface

Core Concepts

Infrastructure

Context Graph Use Cases

Meta Agent Context Graph Tools

Use Case 1: AWS IAM Permission Analysis

Example Prompt

What Happens

Sample Generated Queries

Results

Use Case 2: Dependency Impact Analysis

Example Prompt

What Happens

Sample Generated Query

Use Case 3: Security Vulnerability Correlation

Example Prompt

What Happens

Sample Generated Query

Use Case 4: Cross-Account Resource Discovery

Example Prompt

Sample Generated Query

Use Case 5: Creating Custom Relationships

Example Prompt

What Happens

Use Case 6: GitHub Repository Analysis

Example Prompt

Sample Generated Query

Best Practices

Writing Effective Prompts

Example Good Prompts

What’s Next

​Meta Agent Context Graph Tools

​Use Case 1: AWS IAM Permission Analysis

​Example Prompt

​What Happens

​Sample Generated Queries

​Results

​Use Case 2: Dependency Impact Analysis

​Example Prompt

​What Happens

​Sample Generated Query

​Use Case 3: Security Vulnerability Correlation

​Example Prompt

​What Happens

​Sample Generated Query

​Use Case 4: Cross-Account Resource Discovery

​Example Prompt

​Sample Generated Query

​Use Case 5: Creating Custom Relationships

​Example Prompt

​What Happens

​Use Case 6: GitHub Repository Analysis

​Example Prompt

​Sample Generated Query

​Best Practices

​Writing Effective Prompts

​Example Good Prompts

​What’s Next

Meta Agent Context Graph Tools

Use Case 1: AWS IAM Permission Analysis

Example Prompt

What Happens

Sample Generated Queries

Results

Use Case 2: Dependency Impact Analysis

Example Prompt

What Happens

Sample Generated Query

Use Case 3: Security Vulnerability Correlation

Example Prompt

What Happens

Sample Generated Query

Use Case 4: Cross-Account Resource Discovery

Example Prompt

Sample Generated Query

Use Case 5: Creating Custom Relationships

Example Prompt

What Happens

Use Case 6: GitHub Repository Analysis

Example Prompt

Sample Generated Query

Best Practices

Writing Effective Prompts

Example Good Prompts

What’s Next