PackagePublished package

@pasar6987/sf-automotive-fleet

Name: Semantic model package @pasar6987/sf-automotive-fleet
Creator: pasar6987

Fleet composition and participant tracking for commercial and rental vehicle operations.

OSISchema 0.1.1Domain crm Source developer.salesforce.com/docs/atlas.en-us.object_reference.meta/object_reference

Published package · Latest published 1.0.1 Mar 4, 2026 · 3 datasets / 2 measures in the latest review · Updated Mar 11, 2026

Release path

1.0.1Published Mar 4, 2026

Publisher

@pasar6987Published Mar 4, 2026

Structure snapshot

3 datasets2 measures · 29 dimensions

Semantic Graph

Relationship counts appear after the graph loads.

Loading graph

Package graph is loading

Package relationships will appear when the summary is ready.

Reference context

Secondary package facts stay compact

Updated: Mar 11, 2026
Visibility: Public hub listing
License: MIT
Created: Mar 4, 2026

Reference facts

Secondary package facts after the usage path is clear

Licensing, categorization, ownership, and linked metadata stay below the runnable path so the page reads in the right order.

Format

OSI

Upstream

developer.salesforce.com/docs/atlas.en-us.object_reference.meta/object_reference

Repository

Not linked

Domain

crm

Source

developer.salesforce.com/docs/atlas.en-us.object_reference.meta/object_reference

Owner

@pasar6987

Organization

Independent

License

MIT

Visibility

Public hub listing

Publisher

@pasar6987Published Mar 4, 2026

Latest published version

1.0.1Published Mar 4, 2026

Use this package in code and AI

After structure review, move straight into typed reads with load() or compact LLM context with to_prompt().

Python SDK

Python example for @pasar6987/sf-automotive-fleet

This example uses the current package ref and, when preview data is available, fills in real dataset names from the published summary.

import rawctx

model = rawctx.load("@pasar6987/sf-automotive-fleet")
prompt = rawctx.to_prompt(
    "@pasar6987/sf-automotive-fleet",
    datasets=["Fleet", "FleetAsset"],
    max_tokens=2000,
)

print(model.datasets)        # ["Fleet", "FleetAsset", "FleetParticipant"]
print(model.measures)        # [Measure(name="Fleet.ActiveAssetCount", ...), Measure(name="FleetAsset.AssetUsage", ...)]
print(model.dimensions)      # [Dimension(name="CurrentOwnerId", ...), Dimension(name="EffectiveEndDate", ...), Dimension(name="EffectiveStartDate", ...)]
print(model.relationships)   # [Relationship(name='...', ...)]
print(prompt)

See Python docs

README

Package narrative and examples

Use documentation after the package clears provenance, ownership, and runnable-path checks.

@pasar6987/sf-automotive-fleet

Fleet composition and participant tracking for commercial and rental vehicle operations.

Overview

	Count
Objects (Datasets)	3
Dimensions	29
Measures	2
Relationships	0

Objects

Fleet — Represents a group of assets used in commercial, service, or transport operations in the manufacturing industry.
FleetAsset — Represents the relationship between an asset and the fleet to which it belongs.
FleetParticipant — Represents the relationship between a fleet and a participant, such as an account, a contact, or a user.

Install

rawctx snapshot-download @pasar6987/sf-automotive-fleet

Structure review

Inspect package structure after the usage path is clear

Use the structural review when you need the package footprint, field counts, and model paths before a deeper explorer pass.

Models1

datasets3

measures2

dimensions29

relationships0

AI context1

models/sf-automotive-fleet.osi.yamlAI context included

3 datasets2 measures29 dimensions0 relationships