Recipes
Six worked examples — each one a real prompt you can paste into Claude Desktop after connecting, plus the underlying MCP tool calls so you can see what your model is actually doing.
Pulls the most recent maintenance-task completion for an item, filtered by service type.
MCP tool call:
{
"tool": "prism_entity_crud",
"args": {
"mega_tool": "entity_crud",
"app": "spare_parts",
"entity": "maintenance_task_completion",
"operation": "list",
"filters": {
"item__name__icontains": "Generator 1",
"task__service_type": "oil_change"
},
"ordering": "-completed_at",
"page_size": 1
}
}
Sample response shape:
{
"success": true,
"data": {
"results": [{
"id": "...",
"completed_at": "2026-04-12T10:00:00Z",
"performed_by": "Wilson, J.",
"operating_hours": 1284,
"notes": "Standard 250-hour oil change. Filter replaced."
}],
"pagination": { "count": 1, "page": 1 }
}
}
Try it: In Claude Desktop, ask: "When was the last oil change on Generator 1?"
Creates a new work order for a maintenance item. Demonstrates a write operation with required fields.
MCP tool call:
{
"tool": "prism_entity_crud",
"args": {
"mega_tool": "entity_crud",
"app": "spare_parts",
"entity": "work_order",
"operation": "create",
"data": {
"title": "Fire pump inspection",
"item_id": "<fire-pump-uuid>",
"priority": "medium",
"description": "Quarterly inspection per NFPA 25.",
"due_date": "2026-05-19"
}
}
}
Try it: "Open a work order to inspect the fire pump next week."
Demonstrates tool chaining: query overdue invoices, then dispatch a templated email.
Step 1 — Query overdue invoices:
{
"tool": "prism_entity_crud",
"args": {
"mega_tool": "entity_crud",
"app": "finance",
"entity": "invoice",
"operation": "list",
"filters": {
"status": "open",
"due_date__lt": "today"
},
"ordering": "due_date",
"page_size": 50
}
}
Step 2 — Email a summary to the finance inbox:
{
"tool": "prism_notification_send",
"args": {
"mega_tool": "notification_send",
"app": "core",
"entity": "artifact_email",
"operation": "send",
"to": ["[email protected]"],
"subject": "Overdue invoices — week of {{week_of}}",
"body": "Top 10 overdue:\n\n{{rendered_table}}\n\nFull list attached.",
"attachments": [{"name": "overdue.csv", "content_b64": "..."}]
}
}
Try it: "Show me all overdue invoices, then email finance a summary."
Combines semantic-search with a follow-up read for full-text retrieval.
Step 1 — Search:
{
"tool": "prism_document_op",
"args": {
"mega_tool": "document_op",
"app": "documents",
"entity": "document",
"operation": "search",
"query": "GIE turbocharger",
"limit": 5
}
}
Step 2 — Read the top hit:
{
"tool": "prism_entity_crud",
"args": {
"mega_tool": "entity_crud",
"app": "documents",
"entity": "document",
"operation": "read",
"id": "<top-result-uuid>"
}
}
Try it: "Find documents about GIE turbocharger and summarize the top result."
Most MCP servers expose CRUD. Cognethics also exposes agentic primitives — spawn a long-running agent with its own budget, persona, and authority level. The agent runs on the platform, delegates to sub-agents as needed, and reports back asynchronously when the mission completes. The calling model gets back a mission ID it can poll, not a blocking response.
Single spawn call (the tease):
{
"tool": "pj_v3_spawn_agent",
"args": {
"mission_intent": "Audit spare-parts inventory: identify items with no service history in 12+ months and items with stock below reorder threshold.",
"persona": "DocIntel",
"authority_level": "delegate",
"budget_usd": 5.0
}
}
Full walkthrough: see
/recipes/spawn-agent/ for the end-to-end agent-OS round-trip —
mission → spawn → budget → wait → fold → audit, with the full HTTP shape for each call.
Want more? Browse the full handler catalog — every handler can be combined into custom recipes.