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Builds comprehensive data inventory per GDPR Art. An agent skill from mukul975/Privacy-Data-Protection-Skills.
Install Data Inventory Mapping
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mapping --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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/data-inventory-mapping .claude/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.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/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .claude/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mappingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mapping --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/privacy/data-inventory-mapping .agents/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .agents/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mapping --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/privacy/data-inventory-mapping .cursor/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .cursor/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Privacy-Data-Protection-Skills.git --path skills/privacy/data-inventory-mapping--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mapping --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/privacy/data-inventory-mapping .gemini/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .gemini/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mappingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/privacy/data-inventory-mapping .github/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .github/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-inventory-mapping --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/privacy/data-inventory-mapping .opencode/skills/data-inventory-mapping && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "data-inventory-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-inventory-mapping into .opencode/skills/data-inventory-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-inventory-mapping", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
data-inventory-mapping- GitHub stars
- 295
- Token cost
- ~2.8k tokens
- SKILL.md length
- 1,154 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 278
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Builds comprehensive data inventory per GDPR Art. An agent skill from mukul975/Privacy-Data-Protection-Skills.
- Works in 5 steps: System Discovery (Weeks 1-3) → Data Element Mapping (Weeks 3-6) → Data Flow Mapping (Weeks 6-9) → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, Art. 30 Required Content for…, Data Inventory Construction… and Data Flow Diagram Standards, plus 2 more sections
- Runs Python scripts from its folder
What it does
Data Inventory Mapping is an agent skill from mukul975/Privacy-Data-Protection-Skills. Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.
Its SKILL.md is about 2.8k 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 data-inventory-mapping skill to build comprehensive data inventory per GDPR Art. An agent skill from mukul975/Privacy-Data-Protection-Skills”
- “/data-inventory-mapping”
Requirements
- Python 3
Workflow steps
5 steps, taken from the step headings in SKILL.md.
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
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Data Inventory Mapping loads about 2.8k tokens when it runs, and up to ~5.6k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 1,154 words of instructions outside code blocks.
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). 1,154 words, ~2,758 tokens.
Download SKILL.mdSave it as
.claude/skills/data-inventory-mapping/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- data-inventory-mapping
- description
- Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- data-classification
- metadata.tags
- data-inventory, data-mapping, art-30, ropa, data-flow, processing-activities
Data Inventory and Mapping for Classification
Overview
A data inventory is the foundational artefact for privacy compliance, providing a structured catalogue of all personal data processing activities across the organisation. GDPR Article 30 mandates that controllers maintain Records of Processing Activities (RoPA) containing specific fields including categories of personal data, purposes of processing, categories of recipients, and transfers to third countries. This skill focuses on building the data inventory that feeds into the RoPA, with emphasis on system-by-system discovery, data flow mapping, classification linkage, and legal basis assignment per data category.
Art. 30 Required Content for Controllers — Art. 30(1)
| Required Field | Description | Classification Relevance |
|---|---|---|
| (a) Controller identity | Name and contact details of controller, joint controller, representative, DPO | Administrative — not classification-dependent |
| (b) Purposes of processing | Specific purpose for each processing activity | Purpose determines applicable lawful basis and drives classification-to-handling mapping |
| (c) Categories of data subjects | Types of individuals whose data is processed (customers, employees, applicants) | Data subject category affects applicable protections (e.g., children, employees) |
| (d) Categories of personal data | Types of personal data processed per activity | Direct output of data classification — personal, special category, criminal |
| (e) Categories of recipients | Who receives the data, including processors | Determines transfer and sharing controls |
| (f) Transfers to third countries | International transfers and safeguard mechanisms | Triggers Chapter V compliance requirements |
| (g) Retention periods | Envisaged time limits for erasure of different categories | Classification tier drives retention policy |
| (h) Security measures | General description of Art. 32 technical and organisational measures | Classification tier determines security control level |
Data Inventory Construction Methodology
Phase 1: System Discovery (Weeks 1-3)
Step 1: Enterprise Application Inventory
Build a complete list of systems that process personal data:
| Discovery Method | Sources | Output |
|---|---|---|
| IT asset management system | CMDB, ServiceNow, Lansweeper | Registered applications and servers |
| Procurement records | Vendor contracts, SaaS subscriptions, licence management | Third-party systems processing data |
| Network traffic analysis | Firewall logs, proxy logs, DNS queries | Undocumented data flows to external services |
| Shadow IT discovery | Cloud access security broker (CASB) logs, expense reports for SaaS tools | Unauthorised or unknown applications |
| Department interviews | Business unit leads, data stewards | Departmental tools and local databases |
Vanguard Financial Services — System Inventory Example
| System | Type | Department | Data Subjects | Classification Priority |
|---|---|---|---|---|
| Salesforce CRM | SaaS | Sales, Customer Service | Customers, prospects | Tier 1 |
| Workday HR | SaaS | Human Resources | Employees, candidates | Tier 1 |
| ADP GlobalView | SaaS | Payroll | Employees | Tier 1 |
| Oracle Data Warehouse | On-premises | Data Engineering | All subjects | Tier 1 |
| SharePoint Online | SaaS | All departments | All subjects | Tier 1 |
| NICE Actimize | On-premises | Compliance | Customers, counterparties | Tier 1 |
| HID Global Access | On-premises | Facilities | Employees, contractors | Tier 2 |
| Cority Occ Health | SaaS | Occupational Health | Employees | Tier 2 |
| Bloomberg Terminal | SaaS | Trading | Counterparties | Tier 2 |
| Microsoft Teams | SaaS | All departments | Employees, external contacts | Tier 2 |
| Adobe Analytics | SaaS | Marketing | Website visitors | Tier 2 |
| ServiceNow ITSM | SaaS | IT | Employees | Tier 3 |
| Confluence Wiki | SaaS | Engineering | Employees | Tier 3 |
Phase 2: Data Element Mapping (Weeks 3-6)
For each system, document every data element:
Step 2: Schema Extraction
- Structured databases: Extract schema metadata (table names, column names, data types) via SQL metadata queries or data catalogue APIs
- SaaS applications: Use API documentation to enumerate data objects and fields
- Unstructured repositories: Catalogue document types and their typical personal data content
- Automated discovery: Deploy scanning tools to identify PII in all repositories (see
auto-data-discoveryskill)
Step 3: Data Element Classification
For each data element, assign:
- Personal data classification: PERSONAL_DIRECT, PERSONAL_INDIRECT, SPECIAL_CATEGORY, CRIMINAL_ART10, PSEUDONYMISED, ANONYMISED, NON_PERSONAL (see
personal-data-testskill) - Classification tier: Public, Internal, Confidential, Restricted (see
classification-policyskill) - Art. 6 lawful basis: The legal basis for processing this element for each stated purpose
- Art. 9(2) condition: If special category, the specific processing condition
Phase 3: Data Flow Mapping (Weeks 6-9)
Step 4: Intra-System Data Flows
Document how data moves within the organisation:
Customer Onboarding Data Flow — Vanguard Financial Services
Customer ──[web form]──► Salesforce CRM
│
┌─────────┼──────────┐
▼ ▼ ▼
Oracle DW SharePoint Email (welcome)
(analytics) (documents) (notifications)
│
▼
Adobe Analytics
(web behaviour)Step 5: External Data Flows (Third-Party Sharing)
Document all data sharing with external parties:
| Sender System | Recipient | Data Categories | Transfer Mechanism | Legal Safeguard |
|---|---|---|---|---|
| Salesforce CRM | Salesforce Inc. (processor) | Customer personal data | SaaS hosting | Standard Contractual Clauses (2021/914) |
| Workday HR | Workday Inc. (processor) | Employee personal + special category | SaaS hosting | EU-US Data Privacy Framework |
| ADP Payroll | HMRC (statutory recipient) | Employee financial data | Secure file transfer | Legal obligation Art. 6(1)(c) |
| NICE Actimize | NCA (statutory recipient) | Customer AML data (Art. 10) | SAR Online portal | Legal obligation POCA 2002 |
| Oracle DW | Deloitte (auditor) | Anonymised financial data | Encrypted file transfer | Joint controller agreement |
Show full SKILL.md (440 more words)Show less
Phase 4: Legal Basis and Purpose Mapping (Weeks 9-11)
Step 6: Purpose-Basis Matrix
For each processing activity, map data categories to purposes and legal bases:
| Processing Activity | Data Category | Purpose | Art. 6 Basis | Art. 9(2) / Art. 10 |
|---|---|---|---|---|
| Customer account management | Name, email, address, account number | Contract performance | Art. 6(1)(b) | N/A |
| KYC identity verification | Name, DOB, ID documents, address | Legal obligation (MLR 2017) | Art. 6(1)(c) | N/A |
| Employee payroll | Name, NINO, bank details, salary | Contract performance | Art. 6(1)(b) | N/A |
| Employee diversity monitoring | Ethnicity, sexual orientation | Equality monitoring | Art. 6(1)(a) / 6(1)(c) | Art. 9(2)(a) / 9(2)(b) |
| Building access control | Fingerprint template | Physical security | Art. 6(1)(f) | Art. 9(2)(a) |
| AML monitoring | Transaction patterns, SAR data | Legal obligation (POCA 2002) | Art. 6(1)(c) | Art. 10 — DPA Sch.1 Pt.2 para 10 |
| Website analytics | IP address, cookies, browsing | Legitimate interests | Art. 6(1)(f) | N/A |
| Marketing communications | Email, preferences | Consent | Art. 6(1)(a) | N/A |
Phase 5: Documentation and Maintenance (Ongoing)
Step 7: Inventory Consolidation
Consolidate all discovery into the formal data inventory:
- One record per data element per system
- Cross-referenced to processing activities in the RoPA
- Classification labels applied per element
- Review dates set per classification tier
Step 8: Ongoing Maintenance
| Maintenance Activity | Frequency | Responsible |
|---|---|---|
| Automated discovery scan reconciliation | Monthly | Privacy Engineering |
| New system onboarding inventory | Per new system deployment | System Owner + Privacy Analyst |
| Department data steward review | Quarterly | Data Stewards |
| Full inventory accuracy audit | Annually | DPO |
| Classification reclassification review | Annually (borderline: 6-monthly) | Privacy Analyst |
Data Flow Diagram Standards
Notation Convention (Based on DFD Level 0/1)
| Symbol | Meaning |
|---|---|
| Rectangle | External entity (data subject, third party, regulator) |
| Rounded rectangle | Process (system or application) |
| Open rectangle (two parallel lines) | Data store (database, file share) |
| Arrow | Data flow (labelled with data categories) |
| Dashed arrow | Optional or conditional data flow |
| Red border | Contains special category or criminal data |
| Blue border | International transfer |
Enforcement Precedents
- Österreichische Datenschutzbehörde (Austrian DPA) v Local Bakery Chain (2020): EUR 4,000 fine for failure to maintain Art. 30 records. The DPA noted that even small organisations must maintain processing records.
- CNIL v Sergic (2019): EUR 400,000 fine, partly for inadequate data mapping — the controller could not demonstrate it knew where personal data was stored, leading to a data breach going undetected.
- ICO v British Airways (2020): GBP 20 million fine, where inadequate data mapping contributed to delayed breach detection — the controller lacked visibility into personal data flows through its web infrastructure.
Integration Points
- auto-data-discovery: Automated scanning feeds data elements into the inventory
- personal-data-test: Classification decisions applied per data element in the inventory
- special-category-data: Art. 9 data flagged and mapped to processing conditions
- criminal-data-handling: Art. 10 data identified and mapped to national law authorisation
- data-lineage-tracking: Lineage graphs extend the static inventory with dynamic flow information
© 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/data-inventory-mapping 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
Compare with similar skills
Data Inventory Mapping next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Data Inventory Mapping this skillmukul975/Privacy-Data-Protection-Skills | 295 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| C15tc15t/c15t | 1.9k | 1 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| HIPAA Safe Harbor Coverage Auditmaziyarpanahi/openmed | 5.5k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Korean Privacy Termskimlawtech/korean-privacy-terms | 586 | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Gdpr ComplianceSushegaad/Claude-Skills-Governance-Risk-and-Compliance | 942 | 1 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Hipaa ComplianceSushegaad/Claude-Skills-Governance-Risk-and-Compliance | 942 | 1 repos | ~2.3k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Data Inventory Mapping
What does Data Inventory Mapping do?
Builds comprehensive data inventory per GDPR Art. An agent skill from mukul975/Privacy-Data-Protection-Skills. Data Inventory Mapping is an agent skill from mukul975/Privacy-Data-Protection-Skills. Builds comprehensive data inventory per GDPR Art.
When should I use Data Inventory Mapping?
Data Inventory Mapping fits situations like: tasks that involve Privacy and GDPR.
How do I install Data Inventory Mapping in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a claude-code`. Or copy the skill folder (skills/privacy/data-inventory-mapping in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/data-inventory-mapping in your project. Claude Code loads it when a task matches its description.
How do I install Data Inventory Mapping in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-inventory-mapping -a codex`. Or copy the skill folder (skills/privacy/data-inventory-mapping in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/data-inventory-mapping in your project. Codex loads it when a task matches its description.
Can I use Data Inventory Mapping 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 data-inventory-mapping -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-inventory-mapping, .gemini/skills/data-inventory-mapping, .github/skills/data-inventory-mapping and .opencode/skills/data-inventory-mapping in your project.
What does Data Inventory Mapping need to run?
Going by SKILL.md and its folder, Data Inventory Mapping needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Data Inventory Mapping access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Data Inventory Mapping 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 Data Inventory Mapping use?
Data Inventory Mapping 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 Data Inventory Mapping use?
About 2.8k tokens (SKILL.md is roughly 11k 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 2.9k tokens, read only when the agent opens those files.
What are the alternatives to Data Inventory Mapping?
Skills that share tags, products or a category with Data Inventory Mapping: C15t (c15t/c15t, 1.9k stars), HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars), Korean Privacy Terms (kimlawtech/korean-privacy-terms, 586 stars) and Gdpr Compliance (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 942 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Data Inventory Mapping?
mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 295 GitHub stars. The repository holds 278 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.