A high-performance AI agent skill that automatically builds optimized multi-hop Cypher and SPARQL graph queries to discover indirect relationships and complex patterns.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-hop-reasoning-query-builder
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install multi-hop-reasoning-query-builder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Multi-Hop Reasoning Query Builder?
The Multi-Hop Reasoning Query Builder is an advanced tool engineered to construct complex path traversal and graph query structures for knowledge graphs and graph databases. Developers can easily generate queries that explore indirect relationships, uncover hidden networks, and execute multi-hop logic without manually writing tedious traversals. Integrating this skill within Openclaw Skills simplifies graph operations by automating query assembly for platforms like Neo4j (Cypher) and triple stores (SPARQL).
By leveraging this skill, developers avoid common syntax pitfalls and performance issues associated with variable-length path queries. It automatically injects best practices, bounds traversal depths, and ensures result limits are properly configured. This ensures high-throughput, enterprise-grade queries tailored for fraud detection, recommendation engines, supply chain systems, and social network analysis.
Multi-Hop Reasoning Query Builder Use Cases
- Knowledge Graph Exploration: Automate the process of uncovering deep, multi-step connections between entities across complex ontologies.
- Fraud & Security Detection: Trace transactional, financial, or user registration chains up to multiple hops to catch ring-based fraud patterns.
- E-Commerce Recommendation Engines: Construct query logic that finds secondary interests based on customer purchase history and similar user profiles.
- Supply Chain & Logistics Audits: Build path queries to trace materials or dependencies through variable-depth distributor and supplier relationships.
- Social Network Analysis: Calculate degrees of separation, connection paths, and community influences within large-scale networks.
How Multi-Hop Reasoning Query Builder Works
- Request Parsing: The agent receives a natural language query or structured specification describing the target relationship traversal (e.g., 'Find suppliers connected within three hops').
- Pattern Formulation: The skill maps the target nodes and edges, choosing between fixed depth, variable depth, path discovery, or property path patterns.
- Optimization and Constraint Injection: Safety thresholds (such as limiting traversal depth to 3 or 4) and performance limits are appended to prevent memory exhaustion.
- Syntax Generation: The skill compiles the logical plan into a highly-optimized Cypher or SPARQL executable query.
- Complexity Evaluation: The generated query is accompanied by a complexity analysis detailing expected performance impact based on relationship density.
Multi-Hop Reasoning Query Builder Setup
To integrate and configure the Multi-Hop Reasoning Query Builder within Openclaw Skills, run the setup and installation commands via your command line interface.
# Install the multi-hop query builder skill
openclaw install skill multi-hop-reasoning-query-builder
# Link validation and debugging tools to enable path optimization checks
openclaw link-skill graph-query-optimization-assistant
openclaw link-skill graph-query-debugging-tool
After installation, configure your preferred graph query engine (e.g., Neo4j, Apache Jena) in your environment variables to allow seamless schema-aware query generation.
Multi-Hop Reasoning Query Builder Data Schema & Taxonomy
Generated Artifact Taxonomy
The skill organizes its output structures into standardized models to ensure seamless integration with database drivers:
| Output File / Block Type | Format / Target | Description | Key Meta-Properties |
|---|---|---|---|
| Multi-Hop Query | Cypher / SPARQL | Executable query text with explicit structural pattern matches. | depth, direction, relationship_types |
| Path Discovery Query | Cypher (MATCH path = ...) |
Returns complete relationship subgraphs and traversal chains. | max_hops, path_length_metric |
| Parameterized Template | JSON / Cypher Template | Reusable template containing variables for dynamic runtime binding. | variables, indexed_start_node |
| Complexity Analysis | Markdown Report | Performance estimation, safety flags, and execution metrics. | estimated_complexity, warnings |
Metadata Schema
{
"skill": "multi-hop-reasoning-query-builder",
"query_profile": {
"target_language": "cypher",
"max_configured_depth": 3,
"has_filters": true,
"indexes_applied": ["startNodeId"]
}
}
Multi-Hop Reasoning Query Builder Advanced Features
- Variable-Length Path Control: Dynamically enforces minimum and maximum bounds (
*1..3) to optimize performance while searching across flexible connection ranges. - Multi-Directional Traversal: Generates both directed and undirected multi-hop query logic to account for complex semantic patterns.
- Safety-First Complexity Guardrails: Automatically blocks queries with a depth greater than 4 unless strong index filters are specified, protecting databases from expensive CPU and memory spikes.
- Sub-Graph Path Reconstruction: Configures the
shortestPathfunction and path tracking blocks to reconstruct step-by-step visual relationship chains. - Advanced Filter Hooks: Easily integrates inline path matching rules (
ALLorANYpredicates) to skip specific node states or transaction flags during traversal.
SKILL.md
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