| name | graph-schema-studio |
| description | Design, visualise, and edit Neo4j property graph schemas as interactive React artifacts. Use whenever the user wants to design, create, draw, model, or visualise a graph schema, graph data model, Neo4j schema, property graph model, or node-relationship diagram. Handles both custom domains ("design a schema for my e-commerce system") and 32 pre-built Neo4j reference models across Financial Services, Insurance, Healthcare & Life Sciences, Manufacturing, Cybersecurity, and Industry Agnostic use cases. Trigger for "design a graph schema", "Neo4j data model", "property graph", "arrows.app diagram", "reference model", "industry template", "start from the claims fraud model", "patient journey schema", "CMDB", "IAM effective access", "entity resolution", "UBO", "FAERS drug safety", "BOM", or any Neo4j use case. Also trigger when the user uploads an arrows.app JSON or reference-model JSON. Do NOT trigger for graph charts (bar/line/pie), mathematical graphs, or visualising query results.
|
Graph Schema Studio
Generate an interactive React artifact that lets the user visually design a Neo4j property
graph schema — nodes, relationships, labels, and properties — directly in the chat. Works
from a blank custom domain, from one of 32 pre-built Neo4j reference models, or from a JSON
the user uploads.
The one command you will run
Every path goes through a single script:
python3 /mnt/skills/user/graph-schema-studio/scripts/inject.py <input> [output.jsx]
The script auto-detects what <input> is:
- A reference model id (e.g.
claims-fraud, patient-journey) → loads from the bundled catalog
- A file path (e.g.
/home/claude/my_schema.json) → reads that file directly
- Missing or
- → reads JSON from stdin (the usual "cat heredoc | inject.py" pattern)
--list → prints the reference-model catalog--help → prints usage
Default output is /mnt/user-data/outputs/graph-schema-editor.jsx. Pass a .jsx path as the
second argument to override.
Why one script matters: the React template is ~650 lines. Regenerating it token-by-token
for every schema is slow and wasteful. The injector lets you produce only the ~10–30 lines of
JSON that describe the domain — the editor itself is already on disk.
Pick the right path
Match the user's situation:
- User named a reference model ("start from the claims fraud model", "load UBO schema")
→ run
inject.py <model-id>. See Reference model catalog below for the id list.
- User uploaded arrows.app JSON or reference-model JSON
→ run
inject.py /path/to/file.json. The script auto-unwraps {graph: {...}} and
{initialGraph: {...}} containers, so uploaded files typically work unchanged.
- User described a custom domain ("e-commerce", "music streaming", "my manufacturing
process") → write a minimal schema JSON (see Minimal schema shape) and pipe it via stdin.
- Domain is unclear ("help me model my business") → ask ONE clarifying question before
injecting. Never ship the default example.
Custom domains: the stdin pattern
cat <<'EOF' | python3 /mnt/skills/user/graph-schema-studio/scripts/inject.py
{
"nodes": [
{ "caption": "Customer", "properties": { "customerId": "string", "name": "string", "email": "string" } },
{ "caption": "Order", "properties": { "orderId": "string", "total": "float" } },
{ "caption": "Product", "properties": { "sku": "string", "price": "float" } }
],
"relationships": [
{ "type": "PLACED", "from": "Customer", "to": "Order" },
{ "type": "CONTAINS", "from": "Order", "to": "Product", "properties": { "quantity": "integer" } }
]
}
EOF
For more complex or reusable schemas, save the JSON first and pass the path:
cat > /home/claude/my_schema.json <<'EOF'
{ "nodes": [...], "relationships": [...] }
EOF
python3 /mnt/skills/user/graph-schema-studio/scripts/inject.py /home/claude/my_schema.json
Minimal schema shape
Each node needs only caption. Supply properties when you have them. Everything else
is filled in automatically so you can stay terse.
| Field | Required? | Default when omitted |
|---|
caption | yes | — |
properties | no | {} |
id | no | n0, n1, … |
position | no | Circular auto-layout centred on the viewport |
labels | no | [caption] — see Multi-label nodes below |
style.color | no | Cycled through a 10-colour palette |
style.radius | no | 55 |
Each relationship needs type, and either from/to (caption lookup) or
fromId/toId (explicit ids — required when two nodes share a caption).
| Field | Required? | Notes |
|---|
type | yes | UPPER_SNAKE_CASE, e.g. ACTED_IN |
from or fromId | yes | Caption lookup OR explicit id |
to or toId | yes | Caption lookup OR explicit id |
properties | no | {} |
id | no | r0, r1, … |
Any field you supply is respected unchanged — mix fully-specified nodes with minimal ones
freely. Use explicit positions when the user asks for a specific layout, explicit colours
to group nodes visually, explicit ids when captions would collide.
Multi-label nodes
Neo4j supports multiple labels per node — a common pattern is a primary label plus a
type discriminator, e.g. :Account:Internal vs :Account:External, or
:Event:Authentication. Supply a labels array with more than one entry:
{
"nodes": [
{ "caption": "Account", "labels": ["Account", "Internal"], "properties": { "accountNumber": "string" } },
{ "caption": "Account", "labels": ["Account", "External"], "properties": { "accountNumber": "string" } }
],
"relationships": [
{ "type": "TRANSFERRED_TO", "fromId": "n0", "toId": "n1" }
]
}
Invariants the injector enforces:
caption is always the first element of labels. If the user supplies labels out of
order (caption not first), the injector reorders them; in the editor UI the caption
field drives the primary label.- Duplicates and empty/whitespace-only labels are dropped during normalisation.
- Relationship endpoints cannot be resolved by caption when two nodes share one — use
explicit
fromId/toId as in the example above.
What renders on the canvas: the caption is shown big inside the circle, and any
additional labels appear as small pills directly below the circle (arrows.app convention),
styled in the node's colour so they read as "part of the node". Properties continue below
the pills.
What the user edits: the Inspector has a "Caption (primary label)" field and a
comma-separated "Additional labels" field. Editing either preserves the other —
changing "Account" to "BankAccount" keeps Internal intact.
What the exports produce:
- Cypher:
CREATE (n1:Account:Internal {...})
- arrows.app JSON: the full
labels array is preserved unchanged.
Accepted wrapping formats
The injector unwraps these automatically, so user-uploaded files work without preprocessing:
- Bare:
{ "nodes": [...], "relationships": [...] }
- arrows.app:
{ "graph": { "nodes": [...], "relationships": [...] } }
- Reference model:
{ "initialGraph": { "nodes": [...], "relationships": [...] }, ... }
Reference model catalog
Run inject.py --list for the live catalog. Quick keyword map:
Financial Services (13)
| Keyword | Model id |
|---|
| banking, transactions, KYC, base model | transaction-base-model |
| fraud event sequence | fraud-event-sequence |
| regulatory, compliance | regulatory-dependency-mapping |
| mutual fund, investment | mutual-fund-dependency |
| deposit | deposit-analysis |
| account takeover, ATO | account-takeover-fraud |
| facial recognition, biometric | automated-facial-recognition |
| synthetic identity | synthetic-identity-fraud |
| fraud ring, circular payments | transaction-fraud-ring |
| transaction monitoring, AML | transaction-monitoring |
| IEEE-CIS, fraud detection ML | transaction-fraud-detection |
| customer churn, retention, dormancy | customer-churn |
| UBO, beneficial owner, 6AMLD | ubo-company-ownership |
Insurance (2)
| Keyword | Model id |
|---|
| insurance claims, crash for cash | claims-fraud |
| insurance quote, ghost broker | quote-fraud |
Healthcare & Life Sciences (7)
| Keyword | Model id |
|---|
| patient journey, healthcare, OMOP | patient-journey |
| patent, IP intelligence | patent-intelligence |
| publication, KOL | publication-intelligence |
| pharma pipeline, clinical trials landscape | pipeline-intelligence |
| drug safety, pharmacovigilance, FAERS, DDI | drug-safety |
| single-omics, genomics | single-omics |
| multi-omics | multi-omics |
Manufacturing (4)
| Keyword | Model id |
|---|
| EV, route planning | ev-route-planning |
| BOM, bill of materials, CBOM | configurable-bom |
| traceability, requirements, test cases | engineering-traceability |
| process monitoring, critical path | process-monitoring-cpa |
Cybersecurity (3)
| Keyword | Model id |
|---|
| vulnerability, CVE, VPEM | vulnerability-prioritization |
| attack path, lateral movement | attack-path-analysis |
| SBOM, software supply chain | software-supply-chain-security |
Industry Agnostic (3)
| Keyword | Model id |
|---|
| entity resolution, record linkage | entity-resolution |
| CMDB, IT service graph, infrastructure | it-service-graph |
| IAM, RBAC, effective access | iam-effective-access |
When a reference model is injected, the script surfaces its name and source URL — share
these with the user so they know what they're looking at and can dig deeper if needed.
Some reference models include constraints, indexes, or notes fields; when present,
mention them briefly when presenting the artifact.
Presenting the result
Call present_files on /mnt/user-data/outputs/graph-schema-editor.jsx and briefly orient
the user. Keep it short:
- Double-click the canvas (or click "Add Node") to add nodes
- Drag from a node's edge to another node to create a relationship
- Click any element to edit it in the sidebar — label, properties, colour, radius
- Scroll wheel zooms; drag the canvas to pan
- Export → arrows.app JSON or Cypher
What comes next
After the user customises the schema, the typical next steps live in other skills:
- Generate fake data from the schema →
graph-data-generator skill
- Load that data into a Neo4j instance →
graph-neo4j-ingestion skill
When the user signals they're done editing ("done", "looks good", "generate data"),
capture their exported arrows.app JSON if they pasted one, save it to
/home/claude/graph_schema.json, and hand off to graph-data-generator.
Fallback: editing the template directly
If the injector script fails to run (it shouldn't, but check with ls if things look wrong),
you can hand-edit assets/graph-editor-template.jsx by replacing the
const initialGraph = { ... }; block at the top. This generates hundreds of lines of JSX
token-by-token and is significantly slower — always prefer the injector.
Other notes
- The artifact is self-contained — no external dependencies beyond React, which the Claude
artifact runtime provides.
- Exported arrows.app JSON opens in arrows.app and in tools like Neo4j Runway.
- Exported Cypher produces
CREATE statements that run directly in Neo4j Browser.
- Reference models preserve their curated positions and colours verbatim — those were
tuned by Neo4j for readability, so let the user move things around rather than
re-laying them out yourself.
