PackagePublished package

@pasar6987/sf-net-zero-disclosure

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

ESG disclosure frameworks, reporting periods, document management, and external content integration.

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 · 10 datasets / 0 measures in the latest review · Updated Mar 11, 2026

Release path

1.0.1Published Mar 4, 2026

Publisher

@pasar6987Published Mar 4, 2026

Structure snapshot

10 datasets0 measures · 99 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-disclosure

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-disclosure")
prompt = rawctx.to_prompt(
    "@pasar6987/sf-net-zero-disclosure",
    datasets=["ContentLink", "ContentSource"],
    max_tokens=2000,
)

print(model.datasets)        # ["ContentLink", "ContentSource", "Disclosure"]
print(model.measures)        # [Measure(name="measure_a", ...)]
print(model.dimensions)      # [Dimension(name="ContentSourceId", ...), Dimension(name="ContentSourceType", ...), Dimension(name="LastCntntUpdateDateTime", ...)]
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-disclosure

ESG disclosure frameworks, reporting periods, document management, and external content integration.

Overview

	Count
Objects (Datasets)	10
Dimensions	99
Measures	0
Relationships	0

Objects

ContentLink — Represents a reference object with information about its content source.
ContentSource — Represents the data source that's referenced by an object.
Disclosure — Represents the disclosure details that a company shares, which can be included by a user in their response document.
DisclosureDefinition — Represents information that defines a disclosure type, such as details of the publisher or vendor who created or implemented the report.
DisclosureDefinitionVersion — Represents the version information about the disclosure definition.
DisclosureType — Represents the types of disclosures that are done by an individual or an organization and the associated metadata.
DisclsReportingPeriod — Represents a corporate reporting period that is used for stakeholder disclosure reports.
ExternalDocStorageConfig — Represents configuration, which admin makes in setup to specify the drive, path, and named credential to be used for storing documents on external drives.
InfoLibraryExternalDocument — Represents the external document that's used to collaborate on Information Library content.
SearchableReferenceDocument — Represents documents that are referenced to search for answers during documentation authoring, such as ESG disclosures.

Install

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

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

datasets10

measures0

dimensions99

relationships0

AI context1

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

10 datasets0 measures99 dimensions0 relationships