# Query

> Query the VeritasReason knowledge graph using SPARQL, Cypher, keyword search, and structured graph query patterns.

- Skill: `bibinprathap/query` (Agent Skill)
- Install (CLI): `npx skillmds@latest add bibinprathap/query`
- Raw SKILL.md: https://api.skillmd.com/api/skills/bibinprathap/query/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: bibinprathap (https://skillmd.com/u/bibinprathap)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/bibinprathap/query

---


# /veritasreason:query

Run graph queries and search. Usage: `/veritasreason:query <mode> [args]`

`$ARGUMENTS` = query mode + query string or filter.

---

## `sparql <query>`

Execute a SPARQL query against the graph.

```python
from veritasreason.query import QueryEngine

engine = QueryEngine()
results = engine.query_sparql(query)
```

Return: query bindings as a Markdown table.

---

## `cypher <query>`

Execute a Cypher-like query.

```python
results = engine.query_cypher(query)
```

Output: node/relationship results and path summaries.

---

## `search <keywords> [--filter <type>]`

Search graph entities by keyword.

```python
results = engine.search(keywords=keywords, filter_type=filter_type)
```

Return: ranked matches with entity types and relevance scores.