Agent skill

Employee Health Data

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

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management.

Apache-2.0Auto-check passedProductivity & Automation

Install Employee Health Data

skills CLI
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill employee-health-data -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Privacy-Data-Protection-Skills employee-health-data --agent claude-code

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

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

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

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

Facts

Skill name
employee-health-data
GitHub stars
301
Token cost
~3.9k tokens
SKILL.md length
1,884 words
Files
5 (incl. scripts, references, assets)
Skills in repo
280
Repo updated
First seen
Licence
Apache-2.0

At a glance

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management.

  • Works in 3 steps: National law authorisation: The… → Appropriate safeguards: The national law… → Necessity: The processing must be…
  • Tasks that involve Health and fitness tracking
  • SKILL.md covers Overview, Legal Framework, Processing Scenarios and Data Minimisation Framework, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Employee Health Data is an agent skill from mukul975/Privacy-Data-Protection-Skills. Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.

Its SKILL.md is about 3.9k 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 Productivity & Automation, covering Health and fitness tracking. 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 Health and fitness tracking

Example prompts

  • “Use the employee-health-data skill to govern employee health data processing for fitness-for-work assessments, occupational health surveillance…”
  • “/employee-health-data”

Requirements

  • Python 3

Workflow steps

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

  1. National law authorisation: The processing must be authorised by EU or Member State law (not merely the employment contract)
  2. Appropriate safeguards: The national law must provide appropriate safeguards for the fundamental rights and interests of the data subject
  3. Necessity: The processing must be necessary for carrying out obligations — not merely useful

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

Employee Health Data loads about 3.9k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 124 tokens; SKILL.md has 1,884 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~124
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.4k

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). 1,884 words, ~3,859 tokens.

Download SKILL.mdSave it as .claude/skills/employee-health-data/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
employee-health-data
description
Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Applies Art. 9(2)(b) employment obligations and Art. 9(2)(h) health professional exceptions. Covers data minimisation, occupational health provider relationships, and return-to-work procedures. Keywords: health data, Art. 9, occupational health, fitness-for-work, special category, employment, sickness absence.
license
Apache-2.0
metadata.author
mukul975
metadata.version
1.0
metadata.domain
privacy
metadata.subdomain
employee-data-privacy
metadata.tags
health-data, article-9, occupational-health, fitness-for-work, special-category, sickness-absence

Employee Health Data

Overview

Employee health data is among the most sensitive categories of personal data processed in the employment context. It falls under Art. 9(1) GDPR as "data concerning health," defined in Art. 4(15) as "personal data related to the physical or mental health of a natural person, including the provision of health care services, which reveal information about his or her health status." Employers routinely process health data for absence management, fitness-for-work assessments, occupational health surveillance, workplace adjustments for disability, and return-to-work programmes. Each of these processing activities requires identification of a valid Art. 9(2) exception, strict data minimisation, and clear boundaries between what the employer needs to know (fitness/unfitness and any required adjustments) and clinical details (diagnosis, treatment, prognosis) that must remain with the occupational health provider.

Art. 9(2) Exceptions for Employee Health Data
ExceptionArticleEmployment Application
Explicit consentArt. 9(2)(a)Rarely valid due to power imbalance; may apply for genuinely voluntary wellness programmes
Employment law obligationsArt. 9(2)(b)Primary basis: processing necessary for carrying out obligations in employment, social security, and social protection law — to the extent authorised by national law with appropriate safeguards
Vital interestsArt. 9(2)(c)Emergency situations where employee is physically incapacitated and health data is needed for emergency response
Health professional processingArt. 9(2)(h)Processing for preventive or occupational medicine, assessment of working capacity, medical diagnosis — by or under the responsibility of a health professional bound by professional secrecy
Public healthArt. 9(2)(i)Public health threats (pandemic response) — must be based on national or EU law
Substantial public interestArt. 9(2)(g)Where national law establishes a substantial public interest basis, e.g., disability discrimination legislation requiring processing to assess reasonable adjustments
Art. 9(2)(b) — Employment Obligations

This is the most commonly relied upon exception. It requires:

  1. National law authorisation: The processing must be authorised by EU or Member State law (not merely the employment contract)
  2. Appropriate safeguards: The national law must provide appropriate safeguards for the fundamental rights and interests of the data subject
  3. Necessity: The processing must be necessary for carrying out obligations — not merely useful

National implementations:

JurisdictionLegal BasisScope
UKDPA 2018, Schedule 1, Part 1, Para 1Processing necessary for employment obligations including health and safety duties, statutory sick pay, disability adjustments
GermanyBDSG Section 26(3)Processing of special category data for employment purposes where necessary for exercising rights or obligations under employment or social security law
FranceLabour Code Art. L.4624-1 et seq.Occupational health surveillance; employer receives fitness/unfitness conclusion only, not diagnosis
NetherlandsUAVG Art. 30(1)(a)Processing necessary for employment rights and obligations under law or collective agreement
ItalyD.Lgs. 81/2008, Art. 25 and 41Occupational health surveillance; competent doctor (medico competente) conducts assessments and communicates fitness judgment only
Art. 9(2)(h) — Health Professional Exception

Processing is permitted when carried out by or under the responsibility of a health professional subject to professional secrecy. This applies to:

  • Occupational health physicians conducting fitness-for-work assessments
  • Company nurses providing on-site health services
  • Employee Assistance Programme (EAP) counsellors

Critical limitation: The health professional may share with the employer only the conclusion (fit/unfit/fit with adjustments) and not the underlying clinical details. The diagnosis remains confidential between the health professional and the employee.

Processing Scenarios

Scenario 1: Sickness Absence Management

What the employer needs: Dates of absence, whether the absence is certified, expected return date, any workplace adjustments required.

What the employer must not receive: Diagnosis, treatment details, prognosis, medication, mental health specifics.

Data flow:

  1. Employee notifies employer of absence per sickness absence policy
  2. Employee provides a fit note (UK: Statement of Fitness for Work) or equivalent medical certificate from their GP or treating physician
  3. The fit note states: (a) date range, (b) whether the employee is "not fit for work" or "may be fit for work with adjustments," and (c) any recommended adjustments
  4. The employer records: absence dates, fit note dates, adjustment requirements
  5. The employer does not require or record the diagnosis (the diagnosis field on UK fit notes is visible but the employer should not record it in HR systems unless the employee voluntarily shares it for adjustment purposes)

Atlas Manufacturing Group Example: Atlas's sickness absence policy states that employees self-certify for absences up to 7 days and provide a fit note for absences exceeding 7 days. The HR system records absence dates and the fit/unfit conclusion only. The diagnosis field from fit notes is not entered into the HR system. If an employee's absence exceeds 4 weeks, a referral to occupational health is offered — the occupational health report to the employer addresses fitness, adjustments, and anticipated return date, but not clinical diagnosis.

Scenario 2: Fitness-for-Work Assessment

Trigger: Safety-critical roles (drivers, machine operators, work at height), return from long-term absence, concerns about an employee's capacity to perform their role safely.

Data flow:

  1. Employer refers employee to occupational health provider with a specific, written referral question (e.g., "Is the employee fit to operate forklift equipment? Are any workplace adjustments required?")
  2. The referral must not contain health information the employer does not already legitimately hold
  3. The occupational health provider examines the employee (with the employee's cooperation)
  4. The provider issues a report to the employer addressing the referral question only: fit/unfit/fit with adjustments
  5. If adjustments are recommended, they are described functionally (e.g., "reduced lifting to a maximum of 10kg for 6 weeks") without clinical explanation
  6. The employee receives a copy of the report and may request amendments before it is sent to the employer (Access to Medical Reports Act 1988, UK)

Art. 9(2)(h) application: The occupational health provider is a health professional bound by professional secrecy (GMC, NMC, or equivalent registration). The processing is carried out under their responsibility. They share with the employer only what is necessary for the employment decision.

Scenario 3: Occupational Health Surveillance

Scope: Statutory health surveillance required for employees exposed to occupational hazards (noise, vibration, hazardous substances, ionising radiation, asbestos, lead).

Legal basis: Art. 9(2)(b) — legal obligation under national health and safety law implementing Framework Directive 89/391/EEC.

Key obligations:

  • Health surveillance must be conducted by a competent occupational health professional
  • The employer receives a fitness certificate indicating whether the employee is fit for the specific exposure
  • Individual health records are maintained by the occupational health provider, not the employer
  • The employer receives aggregate statistical data (number of employees fit/unfit) for risk assessment purposes
  • Individual results may only be shared with the employer if the employee consents or if national law specifically authorises it
Scenario 4: Disability and Reasonable Adjustments

Legal basis: Art. 9(2)(b) read with national disability discrimination law (UK: Equality Act 2010; EU: Framework Employment Directive 2000/78/EC).

Data minimisation principle: The employer needs to know:

  • That the employee has a condition meeting the legal definition of disability (or may have such a condition)
  • What functional limitations arise from the condition in the work context
  • What adjustments would enable the employee to perform the role

The employer does not need: The specific diagnosis, medication, treatment history, or prognosis — unless the employee voluntarily shares this information to support the adjustment process.

Show full SKILL.md (707 more words)Show less
Scenario 5: COVID-19 Testing and Vaccination (Legacy)

Context: Many organisations implemented COVID-19 testing and vaccination status checking during the pandemic. Residual data and policies may remain.

Current obligations:

  • COVID testing data collected during the pandemic must be reviewed for retention compliance
  • Vaccination status records must be deleted unless ongoing legal obligation requires retention (e.g., healthcare workers in specific jurisdictions)
  • Test results and vaccination records are health data under Art. 9(1)
  • The lawful basis for pandemic processing (typically Art. 9(2)(b) or (i)) may no longer apply as pandemic legal frameworks are revoked

Atlas Manufacturing Group Example: Atlas collected COVID test results and vaccination status during 2020-2022 under Art. 9(2)(b) (UK health and safety legal obligation) and Art. 9(2)(i) (public health). Following the revocation of mandatory testing guidance in 2022, Atlas conducted a retention review and deleted all COVID testing data and vaccination records in March 2023, retaining only aggregate statistical data for occupational health reporting.

Scenario 6: Employee Wellness Programmes

Description: Employer-offered wellness programmes including health risk assessments, fitness challenges, mental health support, and biometric screenings.

Lawful basis: Art. 9(2)(a) explicit consent — wellness programmes are the rare employment scenario where consent may be valid, because:

  • Participation is genuinely voluntary
  • Non-participation has no adverse employment consequences
  • The programme is offered for the employee's benefit

Conditions:

  • Consent must be granular (separate consent for each programme element)
  • The employer must not receive individual health data; a third-party wellness provider should process the data and provide only aggregate anonymised reports to the employer
  • Employees must be able to withdraw at any time
  • Line managers must not know who participates

Data Minimisation Framework

What the Employer May Hold
Data ElementPermittedLawful Basis
Absence datesYesArt. 6(1)(b) contract + Art. 9(2)(b) employment obligation
Fit/unfit conclusionYesArt. 9(2)(b) employment obligation
Required workplace adjustmentsYesArt. 9(2)(b) disability legislation
Occupational health referral correspondenceYesArt. 9(2)(h) health professional
Fitness-for-work certificatesYesArt. 9(2)(b) health and safety obligation
What the Employer Must Not Hold
Data ElementProhibitedReason
Clinical diagnosisYes (unless voluntarily shared)Not necessary for employment decisions
Treatment detailsYesNot necessary; disproportionate intrusion
Medication informationYesNot necessary; may reveal conditions not relevant to work
Mental health counselling recordsYesProcessed under professional secrecy by health professional
GP/hospital recordsYesNo lawful basis for employer access
Genetic test resultsYesArt. 9(1) + Art. 9(4) specific national restrictions

Access Controls for Health Data

Need-to-Know Hierarchy
RoleAccess Level
HR Manager (employee relations)Absence dates, fit/unfit conclusion, adjustment requirements
Line ManagerAbsence dates and expected return date only; no health details
Occupational Health ProviderFull clinical information (under professional secrecy)
DPOAccess to processing records and policy compliance; no individual health data
PayrollAbsence dates for statutory sick pay calculation only
ITNo access to health data content; system administration only
Technical Controls
  • Health data must be stored in a separate, access-controlled area of the HR system (not in the general employee record)
  • Access to health data fields requires specific role permission and is audit-logged
  • Health data must be encrypted at rest (AES-256)
  • Health data must not be included in general HR reporting or analytics
  • Automated alerts must notify the DPO if health data access patterns indicate unusual activity

Enforcement Precedents

AuthorityCaseFine/OutcomeKey Issue
LfDI Hamburg (Germany)H&M, 2020EUR 35,258,707.95Employer systematically recorded employee health details from return-to-work conversations, including diagnoses and family health issues
CNIL (France)SAN-2021-015EUR 150,000Employer collected excessive health data during COVID screening beyond what was legally required
Garante (Italy)Provvedimento 2022-0156Processing restrictedEmployer required employees to disclose diagnosis on sickness absence forms
ICO (UK)Enforcement notice, 2021Processing ordered to ceaseEmployer shared employee mental health data with line managers without necessity or consent
AEPD (Spain)PS/00142/2022EUR 100,000Employer processed employee COVID vaccination status after legal basis expired

Integration Points

  • Employment Consent Limits: Consent for health data processing is constrained in employment (see employment-consent-limits skill).
  • Employee DSAR Response: Health data is frequently requested in employee DSARs (see employee-dsar-response skill).
  • HR System Privacy Config: Health data requires dedicated access controls in HR systems (see hr-system-privacy-config skill).
  • Employee Monitoring DPIA: Wellness programmes with health data require DPIA (see employee-monitoring-dpia skill).
  • Background Check Privacy: Pre-employment health questions are restricted by disability discrimination law (see background-check-privacy 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/employee-health-data 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

Employee Health Data 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.

Employee Health Data compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Employee Health Data this skillmukul975/Privacy-Data-Protection-Skills301—~3.9kAutomated safety check: PassApache-2.0
Coachfelixrieseberg/claude-coach1991 repos~4.9kAutomated safety check: PassMIT
Fitness Analyzerhuifer/WellAlly-health9605 repos~1.3kAutomated safety check: PassMIT
Master Ajahn Chahxr843/Master-skill4471 repos~2kAutomated safety check: PassCC-BY-NC-SA-4.0
Mental Health Analyzerhuifer/WellAlly-health9605 repos~3.2kAutomated safety check: PassMIT
Nutrition Analyzerhuifer/WellAlly-health9605 repos~3.3kAutomated safety check: PassMIT

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Questions about Employee Health Data

What does Employee Health Data do?

Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management. Employee Health Data is an agent skill from mukul975/Privacy-Data-Protection-Skills. Governs employee health data processing for fitness-for-work assessments, occupational health surveillance, COVID testing legacy programmes, and absence management.

When should I use Employee Health Data?

Employee Health Data fits situations like: tasks that involve Health and fitness tracking.

How do I install Employee Health Data in Claude Code?

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

How do I install Employee Health Data in Codex?

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

Can I use Employee Health Data 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 employee-health-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/employee-health-data, .gemini/skills/employee-health-data, .github/skills/employee-health-data and .opencode/skills/employee-health-data in your project.

What does Employee Health Data need to run?

Going by SKILL.md and its folder, Employee Health Data needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Employee Health Data 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 Employee Health Data 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 Employee Health Data use?

Employee Health Data 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 Employee Health Data use?

About 3.9k tokens (SKILL.md is roughly 15k 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 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Employee Health Data?

Skills that share tags, products or a category with Employee Health Data: Coach (felixrieseberg/claude-coach, 199 stars), Fitness Analyzer (huifer/WellAlly-health, 960 stars), Master Ajahn Chah (xr843/Master-skill, 447 stars) and Mental Health Analyzer (huifer/WellAlly-health, 960 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Employee Health Data?

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.