neo4j-gds-skill

Name: neo4j-gds-skill
Author: neo4j-contrib

355installs33forks

How to install neo4j-gds-skill?

neo4j-contrib/neo4j-skills/neo4j-gds-skill

$npx -y skills add neo4j-contrib/neo4j-skills --skill neo4j-gds-skill

Installs into the current project.

Summary

Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher —

Files · 1

View on GitHub

SKILL.md

1	## When to Use
2	- Running GDS algorithms against embedded GDS plugin through Python client (`graphdatascience`)
3	- Running GDS algorithms through `CALL gds.*` Cypher procedures
4	- Aura Pro, self-managed Neo4j, local Neo4j, or offline DBMS with GDS plugin installed
5	- Projecting named in-memory graphs, running centrality/community/similarity/path/embedding algorithms
6	- Chaining algorithms via `mutate` mode; building FastRP → KNN pipelines
7	- Writing node embeddings for Neo4j vector indexes / structural similarity search
8	- Memory estimation before large graph operations
9
10	## When NOT to Use
11	- Aura Graph Analytics Sessions / AGA / `GdsSessions` / `AuraGraphDataScience` → `neo4j-aura-graph-analytics-skill`
12	- AuraDB Cypher API with `{ memory: ... }` or `{ sessionId: ... }` → `neo4j-aura-graph-analytics-skill`
13	- Cypher query authoring → `neo4j-cypher-skill`
14	- Driver/connection setup → `neo4j-driver-python-skill`
15	- GraphRAG retrieval → `neo4j-graphrag-skill`
16	- Creating/querying vector indexes over written embeddings → `neo4j-vector-index-skill`
17
18	\| Context \| Use \|
19	\|---\|---\|
20	\| Aura Pro with GDS plugin \| This skill \|
21	\| Self-managed/local/offline Neo4j with GDS plugin \| This skill \|
22	\| AuraDB serverless analytics session \| `neo4j-aura-graph-analytics-skill` \|
23	\| Self-managed Neo4j attached to AGA session \| `neo4j-aura-graph-analytics-skill` \|
24	\| Non-Neo4j data source \| `neo4j-aura-graph-analytics-skill` \|
25
26	---
27
28	## Pre-flight
29
30	Use only with embedded GDS plugin.
31
32	```python
33	from graphdatascience import GraphDataScience
34
35	gds = GraphDataScience("neo4j+s://xxx.databases.neo4j.io", auth=("neo4j", "pw"), aura_ds=True)
36	gds = GraphDataScience("bolt://localhost:7687", auth=("neo4j", "password"))
37	print(gds.server_version())
38	```
39
40	```cypher
41	RETURN gds.version() AS gds_version
42	```
43
44	If `Unknown function 'gds.version'` → GDS plugin unavailable. AuraDB serverless analytics → `neo4j-aura-graph-analytics-skill`. Self-managed/local → install or enable GDS plugin.
45
46	```bash
47	pip install graphdatascience # Python client
48	pip install graphdatascience[rust_ext] # 3–10× faster serialization
49	```
50
51	Compatibility: graphdatascience v1.22 — GDS >= 2.6 and < 2.28 / < 2026.6, Python >= 3.10 and < 3.15, Neo4j Driver >= 4.4.12 and < 7.0.
52
53	V2 rules:
54	- Prefer `gds.v2.*` when endpoint exists.
55	- Use snake_case endpoints and parameters: `page_rank`, `fast_rp`, `mutate_property`, `write_property`.
56	- Use typed result attributes: `result.write_millis`, not `result["writeMillis"]`.
57	- Use v1 if v2 endpoint missing/incompatible; label fallback.
58
59	---
60
61	## Graph Catalog Operations
62
63	### Native Projection
64
65	```cypher
66	CALL gds.graph.project(
67	'myGraph',
68	['Person', 'City'],
69	{ KNOWS: { orientation: 'UNDIRECTED' }, LIVES_IN: {} }
70	)
71	YIELD graphName, nodeCount, relationshipCount
72	```
73
74	```python
75	G, result = gds.v2.graph.project("myGraph", "Person", "KNOWS")
76	print(result.node_count, result.relationship_count)
77
78	G, result = gds.v2.graph.project(
79	"myGraph",
80	{"Person": {"properties": ["age", "score"]}, "City": {}},
81	{"KNOWS": {"orientation": "UNDIRECTED"}, "LIVES_IN": {"properties": ["since"]}}
82	)
83	```
84
85	Native projection: plugin/simple Python-client workflow only. AGA Sessions → `neo4j-aura-graph-analytics-skill`.
86	V1 fallback: `gds.graph.project(...)`.
87
88	### Cypher Projection (use for new Cypher workflows, filters, transforms)
89
90	```python
91	G, result = gds.graph.cypher.project(
92	"""
93	MATCH (source:Person)-[r:KNOWS]->(target:Person)
94	WHERE source.active = true
95	RETURN gds.graph.project($graph_name, source, target,
96	{ sourceNodeProperties: source { .score }, relationshipType: 'KNOWS' })
97	""",
98	database="neo4j", graph_name="activeGraph"
99	)
100	```
101
102	`gds.graph.cypher.project` must end with one `RETURN gds.graph.project(...)` clause. If validation fails: use `gds.run_cypher(...)`, then `gds.graph.get("graphName")`.
103	Use v1 `gds.graph.cypher.project(...)` if v2 graph projection cannot express required filter/transform.
104
105	AGA Sessions → `neo4j-aura-graph-analytics-skill`; never use plugin Cypher projection.
106
107	### Undirected Projection
108
109	Native projection: set `orientation: 'UN

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neo4j-gds-skill

355installs33forks

View on GitHub

How to install neo4j-gds-skill?

neo4j-contrib/neo4j-skills/neo4j-gds-skill

$npx -y skills add neo4j-contrib/neo4j-skills --skill neo4j-gds-skill

Installs into the current project.

Summary

Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher —

Files · 1

View on GitHub

SKILL.md

1	## When to Use
2	- Running GDS algorithms against embedded GDS plugin through Python client (`graphdatascience`)
3	- Running GDS algorithms through `CALL gds.*` Cypher procedures
4	- Aura Pro, self-managed Neo4j, local Neo4j, or offline DBMS with GDS plugin installed
5	- Projecting named in-memory graphs, running centrality/community/similarity/path/embedding algorithms
6	- Chaining algorithms via `mutate` mode; building FastRP → KNN pipelines
7	- Writing node embeddings for Neo4j vector indexes / structural similarity search
8	- Memory estimation before large graph operations
9
10	## When NOT to Use
11	- Aura Graph Analytics Sessions / AGA / `GdsSessions` / `AuraGraphDataScience` → `neo4j-aura-graph-analytics-skill`
12	- AuraDB Cypher API with `{ memory: ... }` or `{ sessionId: ... }` → `neo4j-aura-graph-analytics-skill`
13	- Cypher query authoring → `neo4j-cypher-skill`
14	- Driver/connection setup → `neo4j-driver-python-skill`
15	- GraphRAG retrieval → `neo4j-graphrag-skill`
16	- Creating/querying vector indexes over written embeddings → `neo4j-vector-index-skill`
17
18	\| Context \| Use \|
19	\|---\|---\|
20	\| Aura Pro with GDS plugin \| This skill \|
21	\| Self-managed/local/offline Neo4j with GDS plugin \| This skill \|
22	\| AuraDB serverless analytics session \| `neo4j-aura-graph-analytics-skill` \|
23	\| Self-managed Neo4j attached to AGA session \| `neo4j-aura-graph-analytics-skill` \|
24	\| Non-Neo4j data source \| `neo4j-aura-graph-analytics-skill` \|
25
26	---
27
28	## Pre-flight
29
30	Use only with embedded GDS plugin.
31
32	```python
33	from graphdatascience import GraphDataScience
34
35	gds = GraphDataScience("neo4j+s://xxx.databases.neo4j.io", auth=("neo4j", "pw"), aura_ds=True)
36	gds = GraphDataScience("bolt://localhost:7687", auth=("neo4j", "password"))
37	print(gds.server_version())
38	```
39
40	```cypher
41	RETURN gds.version() AS gds_version
42	```
43
44	If `Unknown function 'gds.version'` → GDS plugin unavailable. AuraDB serverless analytics → `neo4j-aura-graph-analytics-skill`. Self-managed/local → install or enable GDS plugin.
45
46	```bash
47	pip install graphdatascience # Python client
48	pip install graphdatascience[rust_ext] # 3–10× faster serialization
49	```
50
51	Compatibility: graphdatascience v1.22 — GDS >= 2.6 and < 2.28 / < 2026.6, Python >= 3.10 and < 3.15, Neo4j Driver >= 4.4.12 and < 7.0.
52
53	V2 rules:
54	- Prefer `gds.v2.*` when endpoint exists.
55	- Use snake_case endpoints and parameters: `page_rank`, `fast_rp`, `mutate_property`, `write_property`.
56	- Use typed result attributes: `result.write_millis`, not `result["writeMillis"]`.
57	- Use v1 if v2 endpoint missing/incompatible; label fallback.
58
59	---
60
61	## Graph Catalog Operations
62
63	### Native Projection
64
65	```cypher
66	CALL gds.graph.project(
67	'myGraph',
68	['Person', 'City'],
69	{ KNOWS: { orientation: 'UNDIRECTED' }, LIVES_IN: {} }
70	)
71	YIELD graphName, nodeCount, relationshipCount
72	```
73
74	```python
75	G, result = gds.v2.graph.project("myGraph", "Person", "KNOWS")
76	print(result.node_count, result.relationship_count)
77
78	G, result = gds.v2.graph.project(
79	"myGraph",
80	{"Person": {"properties": ["age", "score"]}, "City": {}},
81	{"KNOWS": {"orientation": "UNDIRECTED"}, "LIVES_IN": {"properties": ["since"]}}
82	)
83	```
84
85	Native projection: plugin/simple Python-client workflow only. AGA Sessions → `neo4j-aura-graph-analytics-skill`.
86	V1 fallback: `gds.graph.project(...)`.
87
88	### Cypher Projection (use for new Cypher workflows, filters, transforms)
89
90	```python
91	G, result = gds.graph.cypher.project(
92	"""
93	MATCH (source:Person)-[r:KNOWS]->(target:Person)
94	WHERE source.active = true
95	RETURN gds.graph.project($graph_name, source, target,
96	{ sourceNodeProperties: source { .score }, relationshipType: 'KNOWS' })
97	""",
98	database="neo4j", graph_name="activeGraph"
99	)
100	```
101
102	`gds.graph.cypher.project` must end with one `RETURN gds.graph.project(...)` clause. If validation fails: use `gds.run_cypher(...)`, then `gds.graph.get("graphName")`.
103	Use v1 `gds.graph.cypher.project(...)` if v2 graph projection cannot express required filter/transform.
104
105	AGA Sessions → `neo4j-aura-graph-analytics-skill`; never use plugin Cypher projection.
106
107	### Undirected Projection
108
109	Native projection: set `orientation: 'UN

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