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Guides systematic mapping of international personal data flows across an organisation.
Install Data Flow Mapping
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-flow-mapping -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-flow-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-flow-mapping .claude/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .claude/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-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-flow-mapping -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-flow-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-flow-mapping .agents/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .agents/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-mapping -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-flow-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-flow-mapping .cursor/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .cursor/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-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-flow-mapping -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills data-flow-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-flow-mapping .gemini/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .gemini/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-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-flow-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-flow-mapping .github/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .github/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-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-flow-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-flow-mapping .opencode/skills/data-flow-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-flow-mapping" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/data-flow-mapping into .opencode/skills/data-flow-mapping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-flow-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-flow-mapping- GitHub stars
- 295
- Token cost
- ~2.6k tokens
- SKILL.md length
- 1,046 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 278
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guides systematic mapping of international personal data flows across an organisation.
- Works in 5 steps: System Inventory → Data Flow Identification → Third-Party Identification → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, Data Flow Inventory Methodology, Data Flow Visualisation and Ongoing Maintenance
- Runs Python scripts from its folder
What it does
Data Flow Mapping is an agent skill from mukul975/Privacy-Data-Protection-Skills. Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.
Its SKILL.md is about 2.6k 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-flow-mapping skill to guide systematic mapping of international personal data flows across an organisation”
- “/data-flow-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 Flow Mapping loads about 2.6k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 1,046 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). 1,046 words, ~2,553 tokens.
Download SKILL.mdSave it as
.claude/skills/data-flow-mapping/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- data-flow-mapping
- description
- Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- cross-border-transfers
- metadata.tags
- data-flow-mapping, international-transfers, data-inventory, transfer-register, gap-analysis
Mapping International Data Flows
Overview
A comprehensive international data flow map is the foundational prerequisite for any cross-border transfer compliance programme. GDPR Article 30 requires controllers and processors to document transfers to third countries or international organisations. Beyond regulatory compliance, a data flow inventory enables identification of unprotected transfers, assignment of appropriate transfer mechanisms, and ongoing monitoring of data movement across jurisdictions. This skill provides a structured methodology for conducting a system-by-system data flow inventory, identifying all third-party recipients, assigning transfer mechanisms, and performing gap analysis.
Data Flow Inventory Methodology
Phase 1: System Inventory
Identify every information system, application, and service that processes personal data within the organisation.
System categories at Athena Global Logistics:
| Category | Systems | Personal Data Processed |
|---|---|---|
| Enterprise Resource Planning | SAP S/4HANA (hosted Frankfurt DC) | Employee data, customer data, supplier data, financial data |
| Transport Management | CargoWise One (SaaS, hosted Sydney) | Customer shipment data, consignee data, customs broker contacts |
| Customer Relationship Management | Salesforce (SaaS, hosted Frankfurt) | Customer contacts, communication history, sales pipeline |
| Human Resources | Workday (SaaS, hosted Dublin) | Employee personal data, payroll, benefits, performance, recruitment |
| Email and Collaboration | Microsoft 365 (SaaS, hosted EU DC) | Employee communications, contacts, calendar, file storage |
| Warehouse Management | Manhattan Associates (hosted Frankfurt DC) | Warehouse worker IDs, shift schedules, access logs |
| Fleet Management | Fleetio (SaaS, hosted US) | Driver names, licence numbers, GPS tracking data, vehicle assignments |
| Customer Portal | Custom web application (hosted Frankfurt DC) | Customer login credentials, shipment tracking, document uploads |
| Analytics Platform | Snowflake (SaaS, hosted Frankfurt) | Aggregated operational data, pseudonymised customer analytics |
| IT Service Management | ServiceNow (SaaS, hosted Amsterdam) | Employee IT tickets, contact details, device assignments |
Phase 2: Data Flow Identification
For each system, trace every flow of personal data that crosses a national border.
Data flow tracing methodology:
- Inbound flows: Where does personal data enter the system from? (user input, API integrations, file imports, email)
- Internal processing: Where is data stored and processed? (primary data centre, disaster recovery site, development/test environments)
- Outbound flows: Where does personal data leave the system to? (third-party integrations, data exports, email transmissions, backup replication)
- Sub-processor chains: For SaaS systems, identify the provider's sub-processors and their locations.
- Support access: Identify any remote support arrangements where third-country support staff may access personal data.
Athena Global Logistics example data flow register (excerpt):
| Flow ID | Source System | Source Location | Destination | Destination Country | Data Categories | Legal Basis for Processing | Transfer Mechanism |
|---|---|---|---|---|---|---|---|
| DF-001 | SAP S/4HANA | Frankfurt, DE | Athena Logistics (HK) Ltd — local SAP instance | Hong Kong SAR | Customer names, addresses, consignment data | Art. 6(1)(b) contract | SCCs Module 1 |
| DF-002 | CargoWise One | Sydney, AU | Athena Global Logistics GmbH — API pull | Australia | Shipment status, consignee details | Art. 6(1)(b) contract | EU adequacy decision (implied — no decision for AU; SCCs Module 2 required) |
| DF-003 | Workday | Dublin, IE | Workday Inc sub-processor (US backup DC) | United States | Employee HR data | Art. 6(1)(b) employment contract | EU-US DPF + SCCs backup |
| DF-004 | Fleetio | Atlanta, US | N/A (primary processing in US) | United States | Driver names, licence numbers, GPS data | Art. 6(1)(f) legitimate interest | EU-US DPF (verify certification) |
| DF-005 | SAP S/4HANA | Frankfurt, DE | Athena Freight Services India — SFTP batch | India | Employee data (payroll, benefits) | Art. 6(1)(b) employment contract | SCCs Module 1 |
| DF-006 | Custom portal | Frankfurt, DE | TransPacific Freight Solutions — API | Hong Kong SAR | Customer shipment data | Art. 6(1)(b) contract | SCCs Module 2 |
| DF-007 | Microsoft 365 | EU DC | Microsoft Corp sub-processors (global) | Multiple (US, SG, IE) | Employee emails, files | Art. 6(1)(b) contract | EU-US DPF (US); SCCs (SG) |
Show full SKILL.md (481 more words)Show less
Phase 3: Third-Party Identification
Catalogue all third parties (processors, sub-processors, joint controllers, independent controllers) that receive personal data through international transfers.
| Third Party | Role | Country | Data Received | Purpose | Contract Reference |
|---|---|---|---|---|---|
| TransPacific Freight Solutions Ltd | Processor | Hong Kong SAR | Customer shipment data | Freight consolidation and customs clearance | DPA-2025-001 |
| CloudVault Asia Pte Ltd | Sub-processor (of TransPacific) | Singapore | Customer shipment data (hosting) | Cloud infrastructure | Sub-processor agreement via TransPacific |
| Pinnacle Data Services Co Ltd | Sub-processor (of TransPacific) | Thailand | Customs documentation data | Data entry and validation | Sub-processor agreement via TransPacific |
| Athena Freight Services India Pvt Ltd | Controller (intra-group) | India | Employee HR data | Local employment administration | Intra-group DPA-2024-005 |
| Workday Inc | Processor | Ireland (primary), US (backup) | Employee HR data | HRIS platform | DPA-WD-2024-001 |
| Fleetio Inc | Processor | United States | Driver data | Fleet management | DPA-FL-2024-003 |
| Microsoft Corporation | Processor | EU, US, Singapore | Employee email and files | Email and collaboration | DPA-MS-2024-001 |
Phase 4: Transfer Mechanism Assignment
For each identified international data flow, assign the appropriate transfer mechanism:
For each flow:
1. Check: Does the destination have an EU adequacy decision?
→ YES: Record "Adequacy Decision" as mechanism. Done.
→ NO: Continue.
2. Check: Is the importer DPF-certified (for US transfers)?
→ YES: Record "EU-US DPF" as mechanism. Recommend SCCs as backup.
→ NO: Continue.
3. Check: Are SCCs in place between the parties?
→ YES: Record "SCCs Module X" as mechanism. Verify TIA completed.
→ NO: Continue.
4. Check: Are BCRs in place covering the transfer?
→ YES: Record "BCRs" as mechanism. Verify scope covers the data.
→ NO: Continue.
5. Check: Does an Art. 49 derogation apply?
→ YES: Record "Art. 49(1)(x)" as mechanism. Document justification.
→ NO: FLAG AS UNPROTECTED TRANSFER — immediate action required.Phase 5: Gap Analysis
Identify transfers that lack a valid transfer mechanism:
| Gap Type | Description | Priority | Remediation |
|---|---|---|---|
| No mechanism | Transfer occurring without any Art. 45/46/49 basis | Critical | Suspend transfer or execute SCCs within 30 days |
| Expired mechanism | SCCs based on superseded 2010/2021 versions; DPF certification expired | High | Renew mechanism within 60 days |
| Missing TIA | SCCs in place but no documented TIA | High | Complete TIA within 30 days |
| Incomplete documentation | Mechanism exists but Annex fields are incomplete | Medium | Complete documentation within 60 days |
| Sub-processor gap | Importer uses sub-processors not covered by SCCs | High | Extend SCC coverage or require importer to execute Module 3 SCCs |
| Undiscovered flow | Data flow identified during mapping that was not previously known | High | Assess, assign mechanism, and document within 30 days |
Data Flow Visualisation
Visualisation Approaches
Geo-map visualisation: Plot data flows on a world map with colour-coded lines:
- Green: Transfer covered by adequacy decision
- Blue: Transfer covered by SCCs/BCRs with completed TIA
- Yellow: Transfer covered by mechanism but TIA pending or in review
- Red: Transfer lacking valid mechanism — immediate action required
System-centric diagram: For each major system, draw a diagram showing all inbound and outbound data flows with destination countries and mechanisms.
Third-party relationship map: Network diagram showing the organisation at the centre with all third parties and data flows radiating outward, grouped by jurisdiction.
Transfer register dashboard: Tabular view with filtering by mechanism type, destination country, risk level, and review status.
Ongoing Maintenance
- Trigger-based updates: Re-map data flows upon: new system implementation, new vendor onboarding, corporate restructuring, new country operations, new data categories.
- Periodic review: Full data flow inventory review at least annually.
- Automated discovery: Implement network monitoring and data loss prevention (DLP) tools to detect undocumented cross-border data flows.
- Integration with RoPA: Data flow map feeds directly into the Art. 30 Records of Processing Activities.
- Integration with vendor register: Third-party data recipients map feeds into the vendor management and DPA tracking system.
© 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-flow-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 Flow 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 Flow Mapping this skillmukul975/Privacy-Data-Protection-Skills | 295 | — | ~2.6k | 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 | 939 | 1 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Hipaa ComplianceSushegaad/Claude-Skills-Governance-Risk-and-Compliance | 939 | 1 repos | ~2.3k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Data Flow Mapping
What does Data Flow Mapping do?
Guides systematic mapping of international personal data flows across an organisation. Data Flow Mapping is an agent skill from mukul975/Privacy-Data-Protection-Skills. Guides systematic mapping of international personal data flows across an organisation.
When should I use Data Flow Mapping?
Data Flow Mapping fits situations like: tasks that involve Privacy and GDPR.
How do I install Data Flow Mapping in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-flow-mapping -a claude-code`. Or copy the skill folder (skills/privacy/data-flow-mapping in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/data-flow-mapping in your project. Claude Code loads it when a task matches its description.
How do I install Data Flow Mapping in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill data-flow-mapping -a codex`. Or copy the skill folder (skills/privacy/data-flow-mapping in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/data-flow-mapping in your project. Codex loads it when a task matches its description.
Can I use Data Flow 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-flow-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-flow-mapping, .gemini/skills/data-flow-mapping, .github/skills/data-flow-mapping and .opencode/skills/data-flow-mapping in your project.
What does Data Flow Mapping need to run?
Going by SKILL.md and its folder, Data Flow Mapping needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Data Flow 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 Flow 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 Flow Mapping use?
Data Flow 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 Flow Mapping use?
About 2.6k tokens (SKILL.md is roughly 10k 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 Data Flow Mapping?
Skills that share tags, products or a category with Data Flow 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, 939 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Data Flow 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.