esg-and-sustainability-regulatory-reporting

Name: esg-and-sustainability-regulatory-reporting
Author: vaquarkhan

19stars4forks

How to install esg-and-sustainability-regulatory-reporting?

vaquarkhan/data-engineering-agent-skills/esg-and-sustainability-regulatory-reporting

$npx -y skills add vaquarkhan/data-engineering-agent-skills --skill esg-and-sustainability-regulatory-reporting

Installs into the current project.

Summary

Guides agents through ESG, sustainability, and regulatory reporting data products. Use when building governed metrics, traceable evidence, and audit-ready data pipelines for frameworks such as CSRD/ESRS, BRSR, climate disclosures, or similar sustainability reporting obligations.

Files · 1

View on GitHub

SKILL.md

1	# ESG And Sustainability Regulatory Reporting
2
3	## Overview
4
5	Use this skill when sustainability reporting becomes a governed data-engineering problem instead of a spreadsheet exercise. It helps agents build traceable data pipelines, materiality and methodology records, value-chain inputs, approval paths, and assurance-ready evidence for ESG or sustainability disclosures.
6
7	## When to Use
8
9	- building data products for `CSRD`, `ESRS`, `BRSR`, climate, or investor-facing sustainability disclosures
10	- managing emissions, workforce, supplier, governance, or value-chain metrics
11	- preparing ESG datasets for audit, assurance, or board reporting
12	- replacing spreadsheet-driven sustainability reporting with governed pipelines
13	- aligning sustainability metrics with finance, ERP, procurement, and operational source systems
14
15	Do not treat ESG reporting as presentation-layer work only.
16
17	## Workflow
18
19	1. Define the reporting perimeter and framework.
20	Clarify:
21	- reporting framework and audience
22	- legal entity and consolidation scope
23	- materiality or relevance process
24	- required disclosures, KPIs, and narrative dependencies
25
26	2. Map each disclosure to source systems and owners.
27	Include:
28	- source documents and systems
29	- transformation logic
30	- estimation or proxy rules
31	- approvers and accountable owners
32	- value-chain or supplier-supplied data
33
34	3. Make methodology versioned and reviewable.
35	Record:
36	- calculation rules
37	- emission factors or external reference sets
38	- thresholds and materiality criteria
39	- change logs
40	- exception handling
41
42	4. Build controls and evidence around the data product.
43	Require:
44	- lineage to source evidence
45	- approval workflow
46	- segregation of duties where needed
47	- reconciliation and reasonableness checks
48	- locked reporting snapshots
49
50	5. Design for assurance and publication.
51	Confirm:
52	- every datapoint can be traced
53	- reported outputs can be regenerated
54	- narrative and metric versions are aligned
55	- publication format and archival requirements are known
56
57	## Common Rationalizations
58
59	\| Rationalization \| Reality \|
60	\| --- \| --- \|
61	\| "The ESG team owns this, not engineering." \| Sustainability reporting becomes an engineering problem once metrics, lineage, controls, and assurance matter. \|
62	\| "We only need annual reporting, so spreadsheets are fine." \| Annual disclosures still require traceability, version control, and repeatable evidence. \|
63	\| "We can clean the data before audit." \| Assurance failures usually come from weak source mapping and methodology control, not last-minute cleanup. \|
64
65	## Red Flags
66
67	- ESG metrics have no accountable data owner
68	- source evidence and published values cannot be traced end to end
69	- methodology changes are made with no version history
70	- value-chain or supplier inputs are used with no provenance or confidence rating
71	- reporting scope and financial consolidation boundaries do not match
72
73	## Verification
74
75	- [ ] Reporting framework, scope, and materiality logic are explicit
76	- [ ] Each KPI is mapped to sources, methodology, and owners
77	- [ ] Lineage, controls, and approval evidence exist
78	- [ ] The reporting output is assurance-ready and reproducible

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esg-and-sustainability-regulatory-reporting

19stars4forks

View on GitHub

How to install esg-and-sustainability-regulatory-reporting?

vaquarkhan/data-engineering-agent-skills/esg-and-sustainability-regulatory-reporting

$npx -y skills add vaquarkhan/data-engineering-agent-skills --skill esg-and-sustainability-regulatory-reporting

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# ESG And Sustainability Regulatory Reporting
2
3	## Overview
4
5	Use this skill when sustainability reporting becomes a governed data-engineering problem instead of a spreadsheet exercise. It helps agents build traceable data pipelines, materiality and methodology records, value-chain inputs, approval paths, and assurance-ready evidence for ESG or sustainability disclosures.
6
7	## When to Use
8
9	- building data products for `CSRD`, `ESRS`, `BRSR`, climate, or investor-facing sustainability disclosures
10	- managing emissions, workforce, supplier, governance, or value-chain metrics
11	- preparing ESG datasets for audit, assurance, or board reporting
12	- replacing spreadsheet-driven sustainability reporting with governed pipelines
13	- aligning sustainability metrics with finance, ERP, procurement, and operational source systems
14
15	Do not treat ESG reporting as presentation-layer work only.
16
17	## Workflow
18
19	1. Define the reporting perimeter and framework.
20	Clarify:
21	- reporting framework and audience
22	- legal entity and consolidation scope
23	- materiality or relevance process
24	- required disclosures, KPIs, and narrative dependencies
25
26	2. Map each disclosure to source systems and owners.
27	Include:
28	- source documents and systems
29	- transformation logic
30	- estimation or proxy rules
31	- approvers and accountable owners
32	- value-chain or supplier-supplied data
33
34	3. Make methodology versioned and reviewable.
35	Record:
36	- calculation rules
37	- emission factors or external reference sets
38	- thresholds and materiality criteria
39	- change logs
40	- exception handling
41
42	4. Build controls and evidence around the data product.
43	Require:
44	- lineage to source evidence
45	- approval workflow
46	- segregation of duties where needed
47	- reconciliation and reasonableness checks
48	- locked reporting snapshots
49
50	5. Design for assurance and publication.
51	Confirm:
52	- every datapoint can be traced
53	- reported outputs can be regenerated
54	- narrative and metric versions are aligned
55	- publication format and archival requirements are known
56
57	## Common Rationalizations
58
59	\| Rationalization \| Reality \|
60	\| --- \| --- \|
61	\| "The ESG team owns this, not engineering." \| Sustainability reporting becomes an engineering problem once metrics, lineage, controls, and assurance matter. \|
62	\| "We only need annual reporting, so spreadsheets are fine." \| Annual disclosures still require traceability, version control, and repeatable evidence. \|
63	\| "We can clean the data before audit." \| Assurance failures usually come from weak source mapping and methodology control, not last-minute cleanup. \|
64
65	## Red Flags
66
67	- ESG metrics have no accountable data owner
68	- source evidence and published values cannot be traced end to end
69	- methodology changes are made with no version history
70	- value-chain or supplier inputs are used with no provenance or confidence rating
71	- reporting scope and financial consolidation boundaries do not match
72
73	## Verification
74
75	- [ ] Reporting framework, scope, and materiality logic are explicit
76	- [ ] Each KPI is mapped to sources, methodology, and owners
77	- [ ] Lineage, controls, and approval evidence exist
78	- [ ] The reporting output is assurance-ready and reproducible

People who liked this also viewed

6 picks

Type