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Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories.
Install Nist Privacy Identify
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill nist-privacy-identify -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills nist-privacy-identify --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/nist-privacy-identify .claude/skills/nist-privacy-identify && 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 "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .claude/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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/nist-privacy-identifyType 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 nist-privacy-identify -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills nist-privacy-identify --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/nist-privacy-identify .agents/skills/nist-privacy-identify && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .agents/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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 nist-privacy-identify -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills nist-privacy-identify --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/nist-privacy-identify .cursor/skills/nist-privacy-identify && 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 "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .cursor/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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/nist-privacy-identify--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 nist-privacy-identify -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills nist-privacy-identify --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/nist-privacy-identify .gemini/skills/nist-privacy-identify && 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 "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .gemini/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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 nist-privacy-identifyInstalls 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 nist-privacy-identify -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/nist-privacy-identify .github/skills/nist-privacy-identify && 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 "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .github/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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 nist-privacy-identify -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 nist-privacy-identify --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/nist-privacy-identify .opencode/skills/nist-privacy-identify && 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 "nist-privacy-identify" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/nist-privacy-identify into .opencode/skills/nist-privacy-identify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nist-privacy-identify", 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
nist-privacy-identify- GitHub stars
- 301
- Token cost
- ~2.3k tokens
- SKILL.md length
- 1,013 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 280
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories.
- Works in 4 steps: Establish Inventory and Mapping (Months… → Business Environment Analysis (Month 2-3) → Risk Assessment (Months 3-5) → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, IDENTIFY Function Structure, NIST PF to GDPR Mapping and Implementation Methodology, plus 1 more section
- Runs Python scripts from its folder
What it does
Nist Privacy Identify is an agent skill from mukul975/Privacy-Data-Protection-Skills. Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Maps NIST PF controls to GDPR requirements for dual-framework compliance. Keywords: NIST Privacy Framework, IDENTIFY function, ID.BE, ID.DA, ID.IM, ID.RA, privacy risk assessment, data actions.
Its SKILL.md is about 2.3k 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 nist-privacy-identify skill to guide implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment…”
- “/nist-privacy-identify”
Requirements
- Python 3
Workflow steps
4 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
Nist Privacy Identify loads about 2.3k tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 101 tokens; SKILL.md has 1,013 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). 1,013 words, ~2,327 tokens.
Download SKILL.mdSave it as
.claude/skills/nist-privacy-identify/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- nist-privacy-identify
- description
- Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Maps NIST PF controls to GDPR requirements for dual-framework compliance. Keywords: NIST Privacy Framework, IDENTIFY function, ID.BE, ID.DA, ID.IM, ID.RA, privacy risk assessment, data actions.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- privacy-impact-assessment
- metadata.tags
- nist-privacy-framework, identify-function, privacy-risk, data-actions
Implementing NIST Privacy Framework IDENTIFY Function
Overview
The NIST Privacy Framework Version 1.0 (January 2020) provides a voluntary enterprise risk management tool structured around five core functions: IDENTIFY, GOVERN, CONTROL, COMMUNICATE, and PROTECT. The IDENTIFY function develops the organisational understanding to manage privacy risk arising from data processing. This skill covers the four IDENTIFY subcategories: Inventory and Mapping (ID.IM), Business Environment (ID.BE), Risk Assessment (ID.RA), and Data Processing Ecosystem Risk Management (ID.DE).
IDENTIFY Function Structure
ID.IM — Inventory and Mapping
Data processing inventory and mapping activities are understood by the organisation.
| Subcategory | Description | Implementation |
|---|---|---|
| ID.IM-P1 | Systems/products/services that process data are inventoried | Maintain a comprehensive register of all systems processing personal data, including SaaS tools, internal databases, and third-party integrations |
| ID.IM-P2 | Owners of systems/products/services are identified | Assign a data processing owner to each system with documented responsibility for privacy compliance |
| ID.IM-P3 | Categories of individuals whose data are processed are inventoried | Map all data subject categories (employees, customers, patients, vendors, website visitors) |
| ID.IM-P4 | Data actions of the systems/products/services are inventoried | Document data lifecycle actions: collection, retention, logging, generation, transformation, use, disclosure, sharing, transmission, disposal |
| ID.IM-P5 | Purposes for data actions are inventoried | Document specific purposes for each data action, aligned with GDPR Art. 5(1)(b) purpose limitation |
| ID.IM-P6 | Data elements within the data actions are inventoried | Catalogue all personal data elements processed per system and per purpose |
| ID.IM-P7 | Environmental factors affecting the data processing ecosystem are understood | Assess external factors: legal/regulatory requirements, industry standards, market expectations, organisational risk tolerance |
| ID.IM-P8 | Data processing is mapped | Create and maintain data flow maps showing how personal data moves through the organisation |
ID.BE — Business Environment
The organisation's mission, objectives, stakeholders, and activities are understood and prioritised.
| Subcategory | Description | Implementation |
|---|---|---|
| ID.BE-P1 | The organisation's role in the data processing ecosystem is identified and communicated | Determine controller/processor/joint controller status for each processing activity |
| ID.BE-P2 | Priorities for organisational mission, objectives, and activities are established and communicated | Align privacy programme with business objectives; ensure privacy is a design requirement |
| ID.BE-P3 | Systems/products/services that support organisational priorities are identified and key requirements communicated | Identify which processing activities are critical to business operations and prioritise privacy investment accordingly |
ID.RA — Risk Assessment
The organisation understands the privacy risks to individuals and how such processing creates privacy risks to the organisation.
| Subcategory | Description | Implementation |
|---|---|---|
| ID.RA-P1 | Contextual factors related to the systems/products/services and data actions are identified | Assess context: relationship with data subjects, data subject expectations, sensitivity, volume, collection method |
| ID.RA-P2 | Data analytic inputs and outputs are identified and evaluated | For data analytics and AI, identify inputs (training data, inference data) and outputs (predictions, scores, decisions) |
| ID.RA-P3 | Potential problems for individuals that arise from data processing are identified | Identify privacy harms: loss of autonomy, discrimination, economic loss, physical harm, reputational damage, loss of trust |
| ID.RA-P4 | Problematic data actions, the likelihood that they occur, and the resulting problems for individuals are identified and assessed | Assess likelihood and severity of each problematic data action — aligned with GDPR DPIA risk assessment |
| ID.RA-P5 | Risk responses are identified and prioritised | For each identified risk, determine response: mitigate, transfer, avoid, accept |
ID.DE — Data Processing Ecosystem Risk Management
The organisation identifies, assesses, and manages privacy risks associated with data processing by third parties.
| Subcategory | Description | Implementation |
|---|---|---|
| ID.DE-P1 | Data processing ecosystem risk management policies, processes, and procedures are identified, established, assessed, and managed | Vendor privacy management programme with due diligence, contractual requirements, and ongoing monitoring |
| ID.DE-P2 | Data processing ecosystem parties are identified, prioritised, and assessed | Map all processors, sub-processors, and third-party recipients with risk rating |
| ID.DE-P3 | Contracts with data processing ecosystem parties are established, maintained, and managed | Art. 28 DPAs with all processors; joint controller arrangements per Art. 26 |
| ID.DE-P4 | Interoperability frameworks or mechanisms are established for data processing ecosystem parties | Standard data formats, APIs, and privacy-preserving data exchange protocols |
| ID.DE-P5 | Data processing ecosystem parties are managed consistent with the organisation's risk strategy | Ongoing processor performance monitoring, audit rights exercise, sub-processor change management |
Show full SKILL.md (368 more words)Show less
NIST PF to GDPR Mapping
| NIST PF Subcategory | GDPR Equivalent | Implementation Overlap |
|---|---|---|
| ID.IM-P1 through P8 | Art. 30 Records of Processing Activities | RoPA fulfils the core inventory and mapping requirements |
| ID.BE-P1 | Art. 26 Joint Controllers, Art. 28 Processors | Role determination aligns directly |
| ID.RA-P1 through P5 | Art. 35 DPIA | DPIA risk assessment methodology maps to NIST risk assessment |
| ID.DE-P1 through P5 | Art. 28 Processor Requirements | Processor governance maps to ecosystem risk management |
Implementation Methodology
Phase 1: Establish Inventory and Mapping (Months 1-3)
- Deploy a data discovery tool to identify personal data across all systems.
- Conduct departmental interviews to identify informal data processing.
- Create the system-level processing inventory (ID.IM-P1, P2).
- Map data subject categories (ID.IM-P3) and data elements (ID.IM-P6).
- Document data actions per system (ID.IM-P4) and purposes (ID.IM-P5).
- Create data flow maps (ID.IM-P8).
- Cross-reference with existing Art. 30 RoPA.
Phase 2: Business Environment Analysis (Month 2-3)
- Determine controller/processor/joint controller roles (ID.BE-P1).
- Align privacy programme priorities with business strategy (ID.BE-P2).
- Identify critical processing activities (ID.BE-P3).
Phase 3: Risk Assessment (Months 3-5)
- For each processing activity, assess contextual factors (ID.RA-P1).
- Identify problematic data actions using the NIST problematic data action taxonomy:
- Appropriation: use of data in ways beyond data subject expectations
- Distortion: use of inaccurate data or misleading inferences
- Induced disclosure: pressure to reveal more data than intended
- Insecurity: inadequate protection of data
- Re-identification: linking anonymised data back to individuals
- Stigmatisation: association with disfavoured groups
- Surveillance: excessive monitoring
- Unanticipated revelation: discovery of information beyond original data
- Unwarranted restriction: limiting access to services based on data
- Assess likelihood and severity for each problematic data action (ID.RA-P4).
- Determine risk responses (ID.RA-P5).
Phase 4: Ecosystem Risk Management (Months 4-6)
- Inventory all third-party data processors and recipients (ID.DE-P2).
- Conduct vendor privacy due diligence assessments.
- Verify DPA compliance for all processors (ID.DE-P3).
- Establish ongoing monitoring programme (ID.DE-P5).
Enforcement Context
While the NIST Privacy Framework is voluntary and not directly enforceable, organisations demonstrating NIST PF implementation show a mature privacy programme that can support GDPR accountability under Art. 5(2) and Art. 24. US state privacy laws (California CPRA, Virginia VCDPA, Colorado CPA) increasingly reference the NIST PF as a compliance resource.
© 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/nist-privacy-identify 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
Nist Privacy Identify 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 |
|---|---|---|---|---|---|---|
| Nist Privacy Identify this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~2.3k | 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 Nist Privacy Identify
What does Nist Privacy Identify do?
Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Nist Privacy Identify is an agent skill from mukul975/Privacy-Data-Protection-Skills.RA risk assessment subcategories.
When should I use Nist Privacy Identify?
Nist Privacy Identify fits situations like: tasks that involve Privacy and GDPR.
How do I install Nist Privacy Identify in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill nist-privacy-identify -a claude-code`. Or copy the skill folder (skills/privacy/nist-privacy-identify in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/nist-privacy-identify in your project. Claude Code loads it when a task matches its description.
How do I install Nist Privacy Identify in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill nist-privacy-identify -a codex`. Or copy the skill folder (skills/privacy/nist-privacy-identify in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/nist-privacy-identify in your project. Codex loads it when a task matches its description.
Can I use Nist Privacy Identify 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 nist-privacy-identify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nist-privacy-identify, .gemini/skills/nist-privacy-identify, .github/skills/nist-privacy-identify and .opencode/skills/nist-privacy-identify in your project.
What does Nist Privacy Identify need to run?
Going by SKILL.md and its folder, Nist Privacy Identify needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Nist Privacy Identify 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 Nist Privacy Identify 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 Nist Privacy Identify use?
Nist Privacy Identify 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 Nist Privacy Identify use?
About 2.3k tokens (SKILL.md is roughly 9.3k 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 415 tokens, read only when the agent opens those files.
What are the alternatives to Nist Privacy Identify?
Skills that share tags, products or a category with Nist Privacy Identify: 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 Nist Privacy Identify?
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.