Agent skill

Ropa Tool Integration

by mukul975 in mukul975/Privacy-Data-Protection-Skills

Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail.

Apache-2.0Auto-check passedLegal & Compliance

Install Ropa Tool Integration

skills CLI
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ropa-tool-integration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Privacy-Data-Protection-Skills ropa-tool-integration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/privacy/ropa-tool-integration .claude/skills/ropa-tool-integration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ropa-tool-integration
GitHub stars
297
Token cost
~4.2k tokens
SKILL.md length
1,132 words
Files
5 (incl. scripts, references, assets)
Skills in repo
280
Repo updated
First seen
Licence
Apache-2.0

At a glance

Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail.

  • Works in 4 steps: Active Directory / Azure AD: Sync… → ServiceNow / Jira: Integrate with IT… → Vendor management: OneTrust Vendorpedia… → …
  • Tasks that involve Privacy and GDPR
  • SKILL.md covers Overview, Platform Comparison for RoPA…, OneTrust Integration and TrustArc Integration, plus 4 more sections
  • Runs Python scripts from its folder; reaches api.trustarc.com and helix-biotech.collibra.com; needs ONETRUST_CLIENT_SECRET

What it does

Ropa Tool Integration is an agent skill from mukul975/Privacy-Data-Protection-Skills. Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail. Covers API-based synchronization, data mapping import, and automated RoPA population from enterprise tools. Activate for RoPA tool setup, OneTrust integration, TrustArc sync, privacy platform configuration.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/standards.md` and `references/workflows.md`).

It sits in Legal & Compliance, covering Privacy and GDPR. The repository describes itself as: 282+ structured privacy & data protection skills for AI agents. GDPR, CCPA, EU AI Act, HIPAA, LGPD, PIPL, DPDP Act. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Privacy and GDPR

Example prompts

  • “Use the ropa-tool-integration skill to integrate Records of Processing Activities with privacy management platforms including OneTrust, TrustArc…”
  • “/ropa-tool-integration”

Requirements

  • Python 3
  • A credential in ONETRUST_CLIENT_SECRET

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Active Directory / Azure AD: Sync organisational structure and department hierarchy to auto-assign processing owners.
  2. ServiceNow / Jira: Integrate with IT service management to trigger RoPA updates from change requests.
  3. Vendor management: OneTrust Vendorpedia links processors to RoPA recipient fields with DPA status tracking.
  4. Data discovery: OneTrust Data Discovery scans databases, file shares, and cloud storage to identify data categories and populate Art…

What it can do on your machine

Read from SKILL.md and the folder at commit 9b2ef9e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.trustarc.com
    • helix-biotech.collibra.com
    • api.datagrail.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ONETRUST_CLIENT_SECRET

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ropa Tool Integration loads about 4.2k tokens when it runs, and up to ~6.5k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 1,132 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Privacy-Data-Protection-Skills at commit 9b2ef9e, republished under its Apache-2.0 licence (© mukul975). 1,132 words, ~4,172 tokens.

Download SKILL.mdSave it as .claude/skills/ropa-tool-integration/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
ropa-tool-integration
description
Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail. Covers API-based synchronization, data mapping import, and automated RoPA population from enterprise tools. Activate for RoPA tool setup, OneTrust integration, TrustArc sync, privacy platform configuration.
license
Apache-2.0
metadata.author
mukul975
metadata.version
1.0
metadata.domain
privacy
metadata.subdomain
records-of-processing
metadata.tags
gdpr, ropa, onetrust, trustarc, collibra, datagrail, integration, api, privacy-tools

RoPA Tool Integration

Overview

Manual RoPA maintenance using spreadsheets is error-prone, does not scale, and lacks the auditability required for accountability under GDPR Art. 5(2). Privacy management platforms such as OneTrust, TrustArc, Collibra, and DataGrail provide purpose-built RoPA capabilities with workflow automation, audit trails, and regulatory reporting. This skill covers the integration architecture, API-based synchronisation, and data mapping strategies for connecting enterprise IT systems with RoPA management platforms.

Platform Comparison for RoPA Management

CapabilityOneTrustTrustArcCollibraDataGrail
Art. 30(1) controller recordsFull support with all 7 fieldsFull supportFull support via data catalogPartial — focuses on data mapping
Art. 30(2) processor recordsFull supportFull supportSupported via custom asset typesLimited
Automated discoveryData discovery module scans systemsPrivacy intelligence scansData catalog integrationsReal-time data mapping
API availabilityREST API with OAuth 2.0REST API with API keyREST API with OAuth 2.0REST API with API key
Workflow automationBuilt-in approval workflowsAssessment-based workflowsGovernance workflowsRequest-driven workflows
Supervisory authority templatesCNIL, ICO, BfDI, AEPD templatesMultiple SA templatesCustom templatesLimited templates
Data mapping integrationConnectors for 500+ systemsIntegration hubNative data catalog connectors1,800+ SaaS connectors
Export formatsJSON, CSV, PDF, XLSXPDF, CSV, XLSXJSON, CSVJSON, CSV
Version controlBuilt-in versioning and audit trailChange logFull lineage and version historyBasic version tracking
DPIA linkageNative linkage to DPIA moduleLinked assessmentsCross-reference via catalogLimited

OneTrust Integration

Architecture

OneTrust's Data Mapping module forms the foundation of its RoPA capability. Processing activities are represented as "Processing Activity" records that map directly to Art. 30(1) fields.

Integration points:

  1. Active Directory / Azure AD: Sync organisational structure and department hierarchy to auto-assign processing owners.
  2. ServiceNow / Jira: Integrate with IT service management to trigger RoPA updates from change requests.
  3. Vendor management: OneTrust Vendorpedia links processors to RoPA recipient fields with DPA status tracking.
  4. Data discovery: OneTrust Data Discovery scans databases, file shares, and cloud storage to identify data categories and populate Art. 30(1)(c).
API Configuration for Helix Biotech Solutions

Base URL: https://helix-biotech.my.onetrust.com/api/

Authentication: OAuth 2.0 client credentials flow.

python
import requests

ONETRUST_BASE_URL = "https://helix-biotech.my.onetrust.com/api"
CLIENT_ID = "helix-ropa-integration"
CLIENT_SECRET_ENV = "ONETRUST_CLIENT_SECRET"  # Stored in vault

def get_access_token(client_id: str, client_secret: str) -> str:
    """Obtain OAuth 2.0 access token from OneTrust."""
    response = requests.post(
        f"{ONETRUST_BASE_URL}/auth/oauth/token",
        data={
            "grant_type": "client_credentials",
            "client_id": client_id,
            "client_secret": client_secret,
        },
        headers={"Content-Type": "application/x-www-form-urlencoded"},
    )
    response.raise_for_status()
    return response.json()["access_token"]

Fetching processing activities:

python
def get_processing_activities(token: str, page: int = 0, size: int = 50) -> dict:
    """Retrieve processing activities from OneTrust Data Mapping."""
    response = requests.get(
        f"{ONETRUST_BASE_URL}/datasubject/v3/processingactivities",
        headers={"Authorization": f"Bearer {token}"},
        params={"page": page, "size": size},
    )
    response.raise_for_status()
    return response.json()

Creating a processing activity:

python
def create_processing_activity(token: str, activity: dict) -> dict:
    """Create a new processing activity record in OneTrust."""
    payload = {
        "name": activity["processing_activity"],
        "description": activity.get("description", ""),
        "organizationId": activity["organization_id"],
        "purposes": [
            {"name": p, "legalBasis": activity.get("lawful_basis", "")}
            for p in activity.get("purposes", [])
        ],
        "dataSubjectCategories": [
            {"name": c} for c in activity.get("data_subject_categories", [])
        ],
        "dataElementCategories": [
            {"name": c} for c in activity.get("personal_data_categories", [])
        ],
        "retentionPeriod": activity.get("retention_periods", ""),
        "securityMeasures": activity.get("security_measures", ""),
    }
    response = requests.post(
        f"{ONETRUST_BASE_URL}/datasubject/v3/processingactivities",
        headers={
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json",
        },
        json=payload,
    )
    response.raise_for_status()
    return response.json()
Field Mapping: OneTrust to Art. 30(1)
Art. 30(1) FieldOneTrust FieldOneTrust Module
Controller identity (a)Organization > Legal EntityOrganization Management
Purposes (b)Processing Activity > PurposesData Mapping
Data subject categories (c)Processing Activity > Data SubjectsData Mapping
Personal data categories (c)Processing Activity > Data ElementsData Mapping
Recipient categories (d)Processing Activity > Third Parties / VendorsData Mapping + Vendorpedia
International transfers (e)Processing Activity > Transfers > Cross BorderData Mapping
Retention periods (f)Processing Activity > RetentionData Mapping
Security measures (g)Processing Activity > Security MeasuresData Mapping

TrustArc Integration

Architecture

TrustArc (formerly TRUSTe) manages RoPA through its Privacy Operations Manager (PrivacyOps) module. Processing activities are documented through structured assessments that map to Art. 30 fields.

Key integration approach:

  1. Assessment-based RoPA: Each processing activity is documented via a structured assessment questionnaire that populates all Art. 30 fields.
  2. Nymity Research integration: TrustArc leverages Nymity's accountability framework to benchmark RoPA completeness against regulatory expectations.
  3. Automated inventory: TrustArc's inventory module connects to IT asset management systems (e.g., ServiceNow CMDB) to discover data processing systems.
API Configuration

Authentication: API key-based.

python
TRUSTARC_BASE_URL = "https://api.trustarc.com/v1"

def get_processing_records(api_key: str, organization_id: str) -> dict:
    """Retrieve RoPA records from TrustArc PrivacyOps."""
    response = requests.get(
        f"{TRUSTARC_BASE_URL}/organizations/{organization_id}/processing-records",
        headers={
            "Authorization": f"Bearer {api_key}",
            "Accept": "application/json",
        },
    )
    response.raise_for_status()
    return response.json()


def create_assessment(api_key: str, organization_id: str, assessment: dict) -> dict:
    """Create a new processing activity assessment in TrustArc."""
    payload = {
        "name": assessment["name"],
        "type": "PROCESSING_ACTIVITY",
        "templateId": assessment.get("template_id", "art30-controller"),
        "assignee": assessment.get("owner_email"),
        "responses": {
            "purposes": assessment.get("purposes", []),
            "dataSubjects": assessment.get("data_subject_categories", []),
            "dataCategories": assessment.get("personal_data_categories", []),
            "recipients": assessment.get("recipient_categories", []),
            "transfers": assessment.get("international_transfers", []),
            "retention": assessment.get("retention_periods", ""),
            "securityMeasures": assessment.get("security_measures", ""),
        },
    }
    response = requests.post(
        f"{TRUSTARC_BASE_URL}/organizations/{organization_id}/assessments",
        headers={
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json",
        },
        json=payload,
    )
    response.raise_for_status()
    return response.json()

Collibra Integration

Architecture

Collibra is a data intelligence platform with a governance-centric approach to RoPA. Processing activities are modelled as assets within the Collibra Data Catalog, with relationships linking them to data sets, systems, business terms, and governance policies.

Key advantages for RoPA:

  1. Data lineage: Collibra traces data flows from source to destination, automatically populating recipient and transfer fields.
  2. Business glossary: Standardised data category definitions prevent inconsistency across RoPA entries.
  3. Governance workflows: Built-in review and approval workflows with audit trail.
  4. Stewardship: Data stewards assigned to assets align with RoPA processing owners.
API Integration
python
COLLIBRA_BASE_URL = "https://helix-biotech.collibra.com/rest/2.0"

def get_processing_activities(token: str) -> dict:
    """Retrieve processing activity assets from Collibra."""
    response = requests.get(
        f"{COLLIBRA_BASE_URL}/assets",
        headers={"Authorization": f"Bearer {token}"},
        params={
            "typeId": "processing-activity-type-id",
            "limit": 100,
            "offset": 0,
        },
    )
    response.raise_for_status()
    return response.json()


def create_processing_activity_asset(token: str, activity: dict) -> dict:
    """Create a processing activity asset in Collibra."""
    payload = {
        "name": activity["name"],
        "typeId": "processing-activity-type-id",
        "domainId": activity["domain_id"],
        "statusId": "draft-status-id",
    }
    response = requests.post(
        f"{COLLIBRA_BASE_URL}/assets",
        headers={
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json",
        },
        json=payload,
    )
    response.raise_for_status()
    asset_id = response.json()["id"]

    # Add attributes for each Art. 30(1) field
    attributes = [
        {"typeId": "purpose-attr-id", "value": "; ".join(activity.get("purposes", []))},
        {"typeId": "retention-attr-id", "value": activity.get("retention_periods", "")},
        {"typeId": "security-measures-attr-id", "value": activity.get("security_measures", "")},
    ]
    for attr in attributes:
        attr["assetId"] = asset_id
        requests.post(
            f"{COLLIBRA_BASE_URL}/attributes",
            headers={
                "Authorization": f"Bearer {token}",
                "Content-Type": "application/json",
            },
            json=attr,
        )

    return {"asset_id": asset_id, "name": activity["name"]}
Collibra Data Model for Art. 30
Art. 30(1) FieldCollibra Asset/Relation TypeCollibra Domain
Controller identity (a)Business Asset > OrganisationGovernance
Purposes (b)Attribute on Processing Activity assetPrivacy
Data subject categories (c)Related asset: Data Subject CategoryPrivacy
Personal data categories (c)Related asset: Data Category (from Business Glossary)Data Catalog
Recipient categories (d)Relation: "shares data with" > Organisation/SystemPrivacy
International transfers (e)Relation: "transfers to" > Geography assetPrivacy
Retention periods (f)Attribute on Processing Activity assetPrivacy
Security measures (g)Related asset: Security ControlIT Governance
Show full SKILL.md (414 more words)Show less

DataGrail Integration

Architecture

DataGrail focuses on real-time data mapping by connecting directly to an organisation's SaaS applications, databases, and internal systems through its integration library (1,800+ connectors). This automated discovery approach populates RoPA fields from live system metadata.

Key integration approach:

  1. System connectors: DataGrail connects to systems (Salesforce, Workday, AWS, Google Workspace) to discover what personal data is stored and where.
  2. Live data map: The data map reflects current processing in real time, reducing staleness risk.
  3. DSR integration: Data subject request execution reveals processing activities, feeding back into RoPA.
API Integration
python
DATAGRAIL_BASE_URL = "https://api.datagrail.io/v1"

def get_data_map(api_key: str) -> dict:
    """Retrieve the live data map from DataGrail."""
    response = requests.get(
        f"{DATAGRAIL_BASE_URL}/data-map",
        headers={
            "Authorization": f"Bearer {api_key}",
            "Accept": "application/json",
        },
    )
    response.raise_for_status()
    return response.json()


def get_system_inventory(api_key: str) -> dict:
    """Retrieve connected system inventory."""
    response = requests.get(
        f"{DATAGRAIL_BASE_URL}/systems",
        headers={
            "Authorization": f"Bearer {api_key}",
            "Accept": "application/json",
        },
    )
    response.raise_for_status()
    return response.json()

Data Mapping Import Strategy

Migration from Spreadsheet to Platform

Many organisations begin with spreadsheet-based RoPA and need to migrate to a platform. The migration process:

  1. Standardise the spreadsheet format: Ensure the existing spreadsheet has consistent column headers mapping to Art. 30(1)(a)-(g) fields.
  2. Export to CSV/JSON: Convert the spreadsheet to a machine-readable format.
  3. Field mapping: Map spreadsheet columns to the target platform's field schema.
  4. Bulk import via API: Use the platform's bulk import API or CSV upload feature.
  5. Validation: Run completeness checks on imported records.
  6. Relationship creation: Establish links between imported records and existing platform objects (organisations, vendors, systems).
Cross-Platform Synchronisation

When multiple privacy tools are in use (e.g., Collibra for data governance and OneTrust for privacy operations), synchronise RoPA data:

  1. Define the system of record: One platform is the authoritative source for each field. For example, Collibra is authoritative for data categories (from the business glossary), while OneTrust is authoritative for purpose and lawful basis.
  2. API-based sync: Schedule hourly or daily sync jobs that read from the source system and update the target.
  3. Conflict resolution: When both systems have been updated independently, the system-of-record value takes precedence.
  4. Audit trail: Log all sync operations for accountability.

Implementation Roadmap for Helix Biotech Solutions

PhaseDurationActivitiesDeliverables
1. Platform selection4 weeksRFP process, vendor demos, security assessment, DPA negotiationSelected platform, executed DPA
2. Configuration6 weeksCustom field setup, template creation, workflow configuration, SA template importConfigured platform
3. Integration4 weeksAPI integration with AD, ServiceNow, Vendorpedia. SSO configuration.Working integrations
4. Data migration3 weeksImport existing spreadsheet RoPA, validate, establish relationshipsMigrated records
5. UAT and training2 weeksUser acceptance testing, training for DPO office and processing ownersTrained users
6. Go-live1 weekCut over from spreadsheet, decommission old processProduction RoPA system
7. OptimisationOngoingAutomated discovery, advanced reporting, cross-platform syncMature RoPA management

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references, assets) in skills/privacy/ropa-tool-integration of mukul975/Privacy-Data-Protection-Skills.

  • SKILL.md
  • assets/template.md
  • references/standards.md
  • references/workflows.md
  • scripts/process.py

Open the folder on GitHubat commit 9b2ef9e

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Questions about Ropa Tool Integration

What does Ropa Tool Integration do?

Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail. Ropa Tool Integration is an agent skill from mukul975/Privacy-Data-Protection-Skills. Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail.

When should I use Ropa Tool Integration?

Ropa Tool Integration fits situations like: tasks that involve Privacy and GDPR.

How do I install Ropa Tool Integration in Claude Code?

Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ropa-tool-integration -a claude-code`. Or copy the skill folder (skills/privacy/ropa-tool-integration in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/ropa-tool-integration in your project. Claude Code loads it when a task matches its description.

How do I install Ropa Tool Integration in Codex?

Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ropa-tool-integration -a codex`. Or copy the skill folder (skills/privacy/ropa-tool-integration in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/ropa-tool-integration in your project. Codex loads it when a task matches its description.

Can I use Ropa Tool Integration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ropa-tool-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ropa-tool-integration, .gemini/skills/ropa-tool-integration, .github/skills/ropa-tool-integration and .opencode/skills/ropa-tool-integration in your project.

What does Ropa Tool Integration need to run?

Going by SKILL.md and its folder, Ropa Tool Integration needs Python for the scripts in its folder and credentials named ONETRUST_CLIENT_SECRET. Our summary lists: Python 3; A credential in ONETRUST_CLIENT_SECRET.

Does Ropa Tool Integration access the network?

SKILL.md names 3 domains. In commands or code: api.trustarc.com, helix-biotech.collibra.com and api.datagrail.io; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Ropa Tool Integration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Ropa Tool Integration use?

Ropa Tool Integration is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ropa Tool Integration use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.3k tokens, read only when the agent opens those files.

What are the alternatives to Ropa Tool Integration?

Skills that share tags, products or a category with Ropa Tool Integration: Data Export (gustavscirulis/snapgrid, 117 stars), Transfer Impact Assessment Tia Oliver Schmidt Prietz (lawve-ai/awesome-legal-skills, 842 stars), C15t (c15t/c15t, 1.9k stars) and HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ropa Tool Integration?

mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 297 GitHub stars. The repository holds 280 skills in this directory. The repository was last updated on March 16, 2026.

Source: mukul975/Privacy-Data-Protection-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.