PackagePublished package

@pasar6987/sf-net-zero-water

Name: Semantic model package @pasar6987/sf-net-zero-water
Creator: pasar6987

Water consumption and footprint tracking for stationary assets and facilities.

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 / 37 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 datasets37 measures · 44 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-net-zero-water

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-net-zero-water")
prompt = rawctx.to_prompt(
    "@pasar6987/sf-net-zero-water",
    datasets=["StnryAssetWaterActvty", "StnryAssetWaterFtprnt"],
    max_tokens=2000,
)

print(model.datasets)        # ["StnryAssetWaterActvty", "StnryAssetWaterFtprnt", "StnryAssetWtrFtprntItm"]
print(model.measures)        # [Measure(name="StnryAssetWaterActvty.CostPerUnit", ...), Measure(name="StnryAssetWaterActvty.Quantity", ...), Measure(name="StnryAssetWaterActvty.QuantityInM3", ...)]
print(model.dimensions)      # [Dimension(name="ActivitySourceType", ...), Dimension(name="ActivityType", ...), Dimension(name="CostCenter", ...)]
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-net-zero-water

Water consumption and footprint tracking for stationary assets and facilities.

Overview

	Count
Objects (Datasets)	3
Dimensions	44
Measures	37
Relationships	0

Objects

StnryAssetWaterActvty — Represents information about the water activities, such as withdrawal, consumption, or discharge that are related to the stationary assets.
StnryAssetWaterFtprnt — Represents information about the total volume of water from the water activities, such as withdrawal, consumption, or discharge that are related to the stationary assets.
StnryAssetWtrFtprntItm — Represents information about the total volume of water from each water activity, such as withdrawal, consumption, or discharge related to the stationary assets. Each water activity is a child record of the stationary asset water footprint object.

Install

rawctx snapshot-download @pasar6987/sf-net-zero-water

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

measures37

dimensions44

relationships0

AI context1

models/sf-net-zero-water.osi.yamlAI context included

3 datasets37 measures44 dimensions0 relationships