# Query

Query Semantica knowledge graphs, in-memory ContextGraph search, SPARQL over RDF...

- Repository: https://github.com/semantica-agi/semantica (14373 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add semantica-agi/semantica --skill query -g -a claude-code -y`
Codex: `npx skills add semantica-agi/semantica --skill query -g -a codex -y`
Cursor: `npx skills add semantica-agi/semantica --skill query -g -a cursor -y`
Gemini CLI: `npx skills add semantica-agi/semantica --skill query -g -a gemini-cli -y`

## Description

Query Semantica knowledge graphs, in-memory ContextGraph search, SPARQL over RDF triple stores, and Cypher over LPG backends.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# /semantica:query

Query the graph. Usage: `/semantica:query <task> [args]`

> Which API you want depends on where the graph lives.

---

## `search "<keywords>"`, the in-memory ContextGraph

This is the one that works with no external server.

```python
import os
from semantica.context import ContextGraph

graph = ContextGraph()
graph.load_from_file(os.path.expanduser("~/.semantica/kg.json"))   # load_from_file does not expand ~

results = graph.query("vendor selection", skip=0, limit=20)
```

Related lookups on the same object:

```python
graph.find_nodes(...)          graph.find_node(...)
graph.find_related_nodes(...)  graph.get_neighbors(node_id)
graph.find_similar_nodes(...)  graph.get_nodes_by_label(label)
```

Decision-specific queries belong to `/semantica:decision`.

---

## `sparql "<query>"`, RDF triple stores

```python
from semantica.triplet_store import TripletStore

store = TripletStore(backend="oxigraph")       # embedded; needs semantica[tripletstore-oxigraph]
# or backend="blazegraph" | "jena" | "rdf4j" with endpoint="http://..."
result = store.execute_query(sparql)
```

For query planning, optimisation, and caching over a backend:

```python
from semantica.triplet_store import QueryEngine, OxigraphStore

# QueryEngine needs an object exposing execute_sparql(), the raw backend,
# not the TripletStore wrapper above (which only exposes execute_query()).
backend = OxigraphStore()

qe = QueryEngine()
plan   = qe.plan_query(sparql)
tuned  = qe.optimize_query(sparql)
result = qe.execute_query(sparql, store_backend=backend)
stats  = qe.get_query_statistics()
```

Blazegraph / Jena / RDF4J need **no** extra, `semantica.triplet_store` speaks
SPARQL over HTTP using the core `requests` dependency.

---

## `cypher "<query>"`, labeled property graphs

```python
from semantica.graph_store import Neo4jStore    # needs semantica[graph-neo4j]

store = Neo4jStore(uri=..., user=..., password=...)
result = store.execute_query(query, parameters={...})
```

The rest: https://github.com/semantica-agi/semantica/blob/HEAD/plugins/skills/query/SKILL.md