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Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules.
Install Dpia Biometric Systems
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill dpia-biometric-systems -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills dpia-biometric-systems --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/dpia-biometric-systems .claude/skills/dpia-biometric-systems && 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 "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .claude/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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/dpia-biometric-systemsType 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 dpia-biometric-systems -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills dpia-biometric-systems --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/dpia-biometric-systems .agents/skills/dpia-biometric-systems && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .agents/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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 dpia-biometric-systems -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills dpia-biometric-systems --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/dpia-biometric-systems .cursor/skills/dpia-biometric-systems && 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 "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .cursor/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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/dpia-biometric-systems--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 dpia-biometric-systems -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills dpia-biometric-systems --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/dpia-biometric-systems .gemini/skills/dpia-biometric-systems && 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 "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .gemini/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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 dpia-biometric-systemsInstalls 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 dpia-biometric-systems -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/dpia-biometric-systems .github/skills/dpia-biometric-systems && 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 "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .github/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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 dpia-biometric-systems -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 dpia-biometric-systems --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/dpia-biometric-systems .opencode/skills/dpia-biometric-systems && 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 "dpia-biometric-systems" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/dpia-biometric-systems into .opencode/skills/dpia-biometric-systems/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dpia-biometric-systems", 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
dpia-biometric-systems- GitHub stars
- 301
- Token cost
- ~2.7k tokens
- SKILL.md length
- 1,158 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 280
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules.
- Works in 4 steps: Define the specific, concrete purpose… → Demonstrate that biometric processing… → Document why less intrusive alternatives… → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, When a DPIA Is Mandatory for…, DPIA Assessment Structure and DPO Consultation Requirements, plus 2 more sections
- Runs Python scripts from its folder
What it does
Dpia Biometric Systems is an agent skill from mukul975/Privacy-Data-Protection-Skills. Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules. Covers facial recognition, fingerprint, iris scanning, voice recognition, and behavioural biometrics. Applies EDPB Guidelines 3/2019, CNIL Reglement Type Biometrie, and ISO/IEC 24745 biometric template protection. Keywords: DPIA biometric, facial recognition, fingerprint, Art. 35, Art. 9, biometric template, special category.
Its SKILL.md is about 2.7k 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 dpia-biometric-systems skill to conduct Data Protection Impact Assessments for biometric identification and authentication systems under…”
- “/dpia-biometric-systems”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Define the specific, concrete purpose (not "security" but "controlling access to pharmaceutical clean room")
- Demonstrate that biometric processing achieves the purpose more effectively than alternatives
- Document why less intrusive alternatives are insufficient (badge sharing documented incidents, PIN security breaches)
- Confirm processing is limited to what is necessary (no function creep, no secondary uses)
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
Dpia Biometric Systems loads about 2.7k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 128 tokens; SKILL.md has 1,158 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). 1,158 words, ~2,675 tokens.
Download SKILL.mdSave it as
.claude/skills/dpia-biometric-systems/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- dpia-biometric-systems
- description
- Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules. Covers facial recognition, fingerprint, iris scanning, voice recognition, and behavioural biometrics. Applies EDPB Guidelines 3/2019, CNIL Reglement Type Biometrie, and ISO/IEC 24745 biometric template protection. Keywords: DPIA biometric, facial recognition, fingerprint, Art. 35, Art. 9, biometric template, special category.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- privacy-impact-assessment
- metadata.tags
- dpia-biometric, facial-recognition, fingerprint, art-35, art-9, biometric-template
DPIA for Biometric Systems
Overview
Biometric data processing for uniquely identifying natural persons falls under GDPR Article 9(1) special category data and triggers a mandatory DPIA under Article 35(3)(b) — "processing on a large scale of special categories of data." The European Data Protection Board (EDPB) Guidelines on DPIA list biometric processing as an inherently high-risk activity requiring assessment regardless of scale. This skill provides a structured DPIA methodology specifically designed for biometric identification and authentication systems.
When a DPIA Is Mandatory for Biometric Systems
Under EDPB WP248rev.01, a DPIA is required when processing meets two or more criteria from the nine-factor list. Biometric systems commonly trigger:
| EDPB Criterion | Biometric Relevance |
|---|---|
| Special category data (Criterion 4) | Biometric data under Art. 9(1) when used for unique identification |
| Systematic monitoring (Criterion 3) | Facial recognition CCTV, continuous gait analysis |
| Large-scale processing (Criterion 5) | Organisation-wide deployment of fingerprint scanners |
| Innovative technology (Criterion 8) | Behavioural biometrics, emotion detection, multimodal biometrics |
| Vulnerable data subjects (Criterion 7) | Employees (power imbalance), children, patients |
| Automated decision-making (Criterion 2) | Biometric-based access decisions without human review |
National DPA blacklists universally include biometric processing:
- CNIL (France): Deliberation 2018-327, List 11 — Biometric processing for identification
- ICO (UK): DPIA required for biometric data processing at any scale
- AEPD (Spain): List includes biometric processing for access control
- BfDI (Germany): All biometric employee processing requires DPIA
DPIA Assessment Structure
Section 1: Processing Description (Art. 35(7)(a))
Document the biometric system in detail:
System Architecture:
- Biometric modality: fingerprint, facial recognition, iris, voice, behavioural, or multimodal
- Capture device specifications: sensor type, resolution, liveness detection capability
- Template extraction algorithm: vendor, version, ISO/IEC 19795 compliance
- Template storage: on-device (token/badge), local server, centralised database, cloud
- Matching architecture: 1:1 verification or 1:N identification
- Integration points: access control, time and attendance, HR systems, CCTV
Data Flows:
- Raw biometric data capture (image, audio, behavioural signal)
- Feature extraction and template creation
- Template storage location and encryption
- Matching and decision process
- Audit logging
- Template deletion and lifecycle
Data Subjects and Scale:
- Number of enrolled individuals
- Number of daily biometric transactions
- Categories of data subjects (employees, visitors, contractors, customers)
- Vulnerable groups affected (employees with power imbalance, children)
Section 2: Necessity and Proportionality (Art. 35(7)(b))
Lawful Basis Assessment:
| Basis | Art. 6(1) | Art. 9(2) | Assessment |
|---|---|---|---|
| Consent | Art. 6(1)(a) | Art. 9(2)(a) | Problematic for employees (power imbalance); may be valid for voluntary customer opt-in |
| Legal obligation | Art. 6(1)(c) | Art. 9(2)(b) | Valid where national law mandates biometric verification (nuclear facilities, pharmaceutical production) |
| Legitimate interest | Art. 6(1)(f) | Not available | Art. 9(2) does not include legitimate interest; must pair with another Art. 9(2) condition |
| Public interest | Art. 6(1)(e) | Art. 9(2)(g) | Valid for border control, law enforcement with Member State law basis |
| Employment law | Art. 6(1)(b) | Art. 9(2)(b) | Valid where national employment law authorises biometric processing with appropriate safeguards |
Necessity Test:
- Define the specific, concrete purpose (not "security" but "controlling access to pharmaceutical clean room")
- Demonstrate that biometric processing achieves the purpose more effectively than alternatives
- Document why less intrusive alternatives are insufficient (badge sharing documented incidents, PIN security breaches)
- Confirm processing is limited to what is necessary (no function creep, no secondary uses)
Proportionality Assessment:
- Severity of the security risk vs. intrusiveness of biometric processing
- Scope: targeted deployment (specific areas/roles) vs. blanket deployment
- Alternative non-biometric method available for those who object
- Safeguards proportionate to the heightened risk of special category data
Section 3: Risk Identification and Assessment (Art. 35(7)(c))
Biometric-Specific Risk Categories:
| Risk ID | Risk Category | Description | Typical Severity |
|---|---|---|---|
| BIO-R1 | Template breach | Unauthorised access to biometric template database; unlike passwords, biometric characteristics cannot be changed | Very High |
| BIO-R2 | Function creep | Biometric data collected for access control repurposed for monitoring, emotion detection, or performance tracking | High |
| BIO-R3 | Discrimination | Biometric system accuracy varies by demographic group (skin tone, age, disability), causing disproportionate false rejections | High |
| BIO-R4 | Covert collection | Facial recognition or behavioural biometrics collected without active data subject participation or awareness | High |
| BIO-R5 | Cross-system linkage | Biometric templates matched across unrelated systems enabling tracking beyond original purpose | Very High |
| BIO-R6 | Spoofing and fraud | Biometric data used to create synthetic representations (deepfakes, artificial fingerprints) | High |
| BIO-R7 | Chilling effect | Employees alter behaviour due to awareness of biometric monitoring, impacting freedom of expression and association | Medium |
| BIO-R8 | Irrevocability | Compromised biometric data cannot be reset like a password; lifetime impact on data subjects | Very High |
Show full SKILL.md (452 more words)Show less
Section 4: Mitigation Measures (Art. 35(7)(d))
Technical Safeguards:
| Measure | Standard Reference | Implementation |
|---|---|---|
| Biometric template protection | ISO/IEC 24745:2022 | Cancelable biometrics or biometric encryption ensuring templates cannot be reverse-engineered to raw data |
| On-device template storage | CNIL Reglement Type Biometrie | Templates stored on employee-held badges/tokens; no centralised database |
| Liveness detection | ISO/IEC 30107 | Anti-spoofing measures: 3D depth sensing, pulse detection, challenge-response |
| Encryption at rest | AES-256 minimum | All biometric templates and audit logs encrypted |
| Encryption in transit | TLS 1.3 | All biometric data transmission between capture device and matching engine |
| Template irreversibility | ISO/IEC 24745 Section 6 | One-way transformation ensuring raw biometric cannot be reconstructed |
| System isolation | Network segmentation | Biometric systems on dedicated VLAN, no internet connectivity |
| Audit logging | Immutable logs | All enrolment, matching, and administrative access events logged |
Organisational Safeguards:
| Measure | Implementation |
|---|---|
| DPIA review cycle | Annual reassessment or upon system change |
| Alternative access method | Non-biometric alternative (PIN + badge) available for all data subjects |
| Employee objection procedure | Formal objection mechanism with no adverse consequences |
| Deletion upon termination | Biometric templates deleted within 24 hours of employment termination |
| Access restriction | Biometric database access limited to named security administrators with MFA |
| Vendor due diligence | Biometric vendor assessed for Art. 28 compliance, subprocessor chain, international transfers |
| Training | All operators trained on biometric system operation and data protection obligations |
| Incident response | Specific breach procedure for biometric data compromise including notification of irrevocability risk |
DPO Consultation Requirements
Under Art. 35(2), the controller shall seek the advice of the DPO when carrying out a DPIA. For biometric systems, the DPO should specifically assess:
- Whether the Art. 9(2) exception is robustly established
- Whether the necessity test has been rigorously applied
- Whether less intrusive alternatives have been genuinely evaluated (not dismissed pro forma)
- Whether the proposed safeguards are adequate for the heightened risk
- Whether Art. 36 prior consultation with the supervisory authority is required
Art. 36 Prior Consultation Triggers
If the DPIA concludes that residual risk remains high after all mitigation measures, the controller must consult the supervisory authority under Art. 36(1) before commencing processing. For biometric systems, prior consultation is typically required when:
- Large-scale facial recognition is deployed in public or semi-public spaces
- Biometric processing involves vulnerable populations (children, patients) without explicit legal basis
- Centralised biometric database stores templates for more than 10,000 individuals
- Biometric system operates in 1:N identification mode across multiple sites
- No adequate alternative to biometric processing can be provided for objecting individuals
Integration Points
- Employee Biometric Data: Detailed guidance on biometric processing in employment (see employee-biometric-data skill)
- DPIA Risk Scoring: Risk scoring methodology for DPIA findings (see dpia-risk-scoring skill)
- DPIA Mitigation Plan: Structured mitigation planning (see dpia-mitigation-plan skill)
- DPIA Stakeholder Consult: Data subject consultation requirements (see dpia-stakeholder-consult skill)
- Employee Monitoring DPIA: Broader employee monitoring assessment (see employee-monitoring-dpia skill)
© 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/dpia-biometric-systems 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
Dpia Biometric Systems 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 |
|---|---|---|---|---|---|---|
| Dpia Biometric Systems this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~2.7k | 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 | 587 | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Gdpr ComplianceSushegaad/Claude-Skills-Governance-Risk-and-Compliance | 946 | 1 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Hipaa ComplianceSushegaad/Claude-Skills-Governance-Risk-and-Compliance | 946 | 1 repos | ~2.3k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Dpia Biometric Systems
What does Dpia Biometric Systems do?
Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules. Dpia Biometric Systems is an agent skill from mukul975/Privacy-Data-Protection-Skills. Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules.
When should I use Dpia Biometric Systems?
Dpia Biometric Systems fits situations like: tasks that involve Privacy and GDPR.
How do I install Dpia Biometric Systems in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill dpia-biometric-systems -a claude-code`. Or copy the skill folder (skills/privacy/dpia-biometric-systems in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/dpia-biometric-systems in your project. Claude Code loads it when a task matches its description.
How do I install Dpia Biometric Systems in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill dpia-biometric-systems -a codex`. Or copy the skill folder (skills/privacy/dpia-biometric-systems in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/dpia-biometric-systems in your project. Codex loads it when a task matches its description.
Can I use Dpia Biometric Systems 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 dpia-biometric-systems -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dpia-biometric-systems, .gemini/skills/dpia-biometric-systems, .github/skills/dpia-biometric-systems and .opencode/skills/dpia-biometric-systems in your project.
What does Dpia Biometric Systems need to run?
Going by SKILL.md and its folder, Dpia Biometric Systems needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Dpia Biometric Systems 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 Dpia Biometric Systems 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 Dpia Biometric Systems use?
Dpia Biometric Systems 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 Dpia Biometric Systems use?
About 2.7k 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 3.7k tokens, read only when the agent opens those files.
What are the alternatives to Dpia Biometric Systems?
Skills that share tags, products or a category with Dpia Biometric Systems: C15t (c15t/c15t, 1.9k stars), HIPAA Safe Harbor Coverage Audit (maziyarpanahi/openmed, 5.5k stars), Korean Privacy Terms (kimlawtech/korean-privacy-terms, 587 stars) and Gdpr Compliance (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dpia Biometric Systems?
mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 301 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.