Translate human-readable natural language questions directly into executable Cypher and SPARQL queries for graph databases and knowledge graphs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install nl-to-graph-query-translator
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 nl-to-graph-query-translator 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 Natural Language to Graph Query Translator?
The Natural Language to Graph Query Translator is a powerful tool within the Openclaw Skills ecosystem designed to bridge the gap between human language and complex graph database operations. It eliminates the need for developers or data analysts to manually construct intricate query syntax, allowing them to interact seamlessly with property graphs and RDF triple stores using plain English text.
By leveraging advanced NLP techniques, this skill interprets the true intent behind natural language inputs and translates them into precise, production-ready graph query statements. This acceleration in workflow dramatically simplifies graph data exploration, query prototyping, and metadata analysis for both technical and non-technical stakeholders.
Natural Language to Graph Query Translator Use Cases
- Convert plain English or human-readable questions into executable graph database queries.
- Generate optimized Cypher queries for property graph databases like Neo4j.
- Construct standard SPARQL queries for RDF triple stores and semantic knowledge graphs.
- Explore multi-hop relationships and complex graph datasets without writing raw query code.
- Rapidly prototype graph patterns and structural queries during application development.
How Natural Language to Graph Query Translator Works
- Identify Entities: The translation engine detects and extracts specific entity names, labels, and types (e.g., people, organizations, locations) from the natural language prompt.
- Identify Relationships: The system processes verbs and connecting phrases to capture semantic relationship directions and types (e.g., "works at", "located in", "purchased").
- Determine Query Type: The input text is classified to determine the structural objective, distinguishing whether the user is querying for specific nodes, intricate relationships, full paths, counts, or numerical aggregations.
- Construct Query Pattern: A structural abstract graph pattern is mapped out internally to mirror the relationships defined by the user's intent.
- Generate Query Syntax: The final abstraction layer generates target syntactic structures, exporting valid, clean Cypher or SPARQL code along with contextual parameter templates.
Natural Language to Graph Query Translator Setup
To install and use this skill within your environment, execute the standard package integration command via your command line interface:
openclaw install nl-to-graph-query-translator
Ensure that your environment variables and graph schemas are mapped correctly in your project configuration file to enable accurate node and relationship mapping.
Natural Language to Graph Query Translator Data Schema & Taxonomy
The skill manages its components and references through a structured taxonomy to maintain accuracy across translations. The system classifies structural query types as follows:
| Output Component | Format / target | Description |
|---|---|---|
| Cypher Query | String (Neo4j syntax) | Executable property graph patterns utilizing MATCH and RETURN clauses. |
| SPARQL Query | String (RDF syntax) | Executable semantic triple statements matching defined URI spaces using SELECT and WHERE. |
| Query Explanations | Markdown Text | Clear structural breakdowns of the translated query logic. |
| Parameter Templates | JSON / Text | Variables extracted from the natural language text to prevent injection vulnerabilities. |
Natural Language to Graph Query Translator Advanced Features
- Multi-Hop Traversal Processing: Advanced logical nesting capable of generating complex deep-path queries spanning multiple entity connections and relationships automatically.
- Parameterized Query Engineering: Automatically isolates variables from query syntax to ensure secure execution and defense against graph injection attacks.
- Dual-Language Syntax Compiling: Seamless switching between Property Graph paradigms (Cypher) and Semantic Web frameworks (SPARQL) based on the target system design.
- Integrated Pipeline Extensibility: Native hooks that allow smooth handoffs to downstream entities, such as the Graph Query Debugging Tool or Graph Query Optimization Assistant.
SKILL.md
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