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Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c).
Install Pia Large Scale Monitor
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill pia-large-scale-monitor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills pia-large-scale-monitor --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/pia-large-scale-monitor .claude/skills/pia-large-scale-monitor && 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 "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .claude/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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/pia-large-scale-monitorType 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 pia-large-scale-monitor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills pia-large-scale-monitor --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/pia-large-scale-monitor .agents/skills/pia-large-scale-monitor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .agents/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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 pia-large-scale-monitor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills pia-large-scale-monitor --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/pia-large-scale-monitor .cursor/skills/pia-large-scale-monitor && 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 "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .cursor/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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/pia-large-scale-monitor--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 pia-large-scale-monitor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills pia-large-scale-monitor --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/pia-large-scale-monitor .gemini/skills/pia-large-scale-monitor && 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 "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .gemini/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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 pia-large-scale-monitorInstalls 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 pia-large-scale-monitor -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/pia-large-scale-monitor .github/skills/pia-large-scale-monitor && 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 "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .github/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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 pia-large-scale-monitor -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 pia-large-scale-monitor --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/pia-large-scale-monitor .opencode/skills/pia-large-scale-monitor && 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 "pia-large-scale-monitor" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/pia-large-scale-monitor into .opencode/skills/pia-large-scale-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pia-large-scale-monitor", 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
pia-large-scale-monitor- GitHub stars
- 301
- Token cost
- ~2.5k tokens
- SKILL.md length
- 1,183 words
- Files
- 5 (incl. scripts, references, assets)
- Skills in repo
- 280
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c).
- Works in 10 steps: CCTV and Video Surveillance → Employee Monitoring → Location Tracking → …
- Tasks that involve Privacy and GDPR
- SKILL.md covers Overview, Regulatory Framework, Monitoring Scenarios and DPIA Methodology for…, plus 1 more section
- Runs Python scripts from its folder
What it does
Pia Large Scale Monitor is an agent skill from mukul975/Privacy-Data-Protection-Skills. Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c). Covers CCTV and video surveillance, employee monitoring, location tracking, internet monitoring, and behavioural analytics. Applies EDPB WP248rev.01 criteria for systematic monitoring of publicly accessible areas. Keywords: DPIA, large-scale monitoring, CCTV, employee monitoring, systematic monitoring, surveillance, location tracking.
Its SKILL.md is about 2.5k 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 pia-large-scale-monitor skill to conduct Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c)”
- “/pia-large-scale-monitor”
Requirements
- Python 3
Workflow steps
10 steps, taken from the step headings in SKILL.md.
- CCTV and Video Surveillance
- Employee Monitoring
- Location Tracking
- Internet and Communications Monitoring
- Behavioural Analytics
- Monitoring Scope Definition (Week 1)
- Necessity and Proportionality Assessment (Week 2)
- Data Subject Impact Assessment (Week 3)
- Technical and Organisational Safeguards (Week 4)
- Documentation and Approval (Week 5)
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
Pia Large Scale Monitor loads about 2.5k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 1,183 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). 1,183 words, ~2,532 tokens.
Download SKILL.mdSave it as
.claude/skills/pia-large-scale-monitor/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- pia-large-scale-monitor
- description
- Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c). Covers CCTV and video surveillance, employee monitoring, location tracking, internet monitoring, and behavioural analytics. Applies EDPB WP248rev.01 criteria for systematic monitoring of publicly accessible areas. Keywords: DPIA, large-scale monitoring, CCTV, employee monitoring, systematic monitoring, surveillance, location tracking.
- license
- Apache-2.0
- metadata.author
- mukul975
- metadata.version
- 1.0
- metadata.domain
- privacy
- metadata.subdomain
- privacy-impact-assessment
- metadata.tags
- dpia, large-scale-monitoring, cctv, employee-monitoring, systematic-monitoring
Privacy Impact Assessment for Large-Scale Monitoring
Overview
GDPR Article 35(3)(c) mandates a DPIA for systematic monitoring of a publicly accessible area on a large scale. The EDPB in WP248rev.01 identifies systematic monitoring as criterion C3, which often combines with other criteria (large scale C4, vulnerable data subjects C7, innovative technology C8) to trigger mandatory DPIA. This skill covers PIA methodology for CCTV/video surveillance, employee monitoring, location tracking, internet/communications monitoring, and behavioural analytics systems.
Regulatory Framework
GDPR Requirements
| Provision | Relevance to Large-Scale Monitoring |
|---|---|
| Art. 35(3)(c) | Mandatory DPIA for systematic monitoring of publicly accessible area on a large scale |
| Art. 35(1) | DPIA required when processing is likely to result in a high risk to rights and freedoms |
| Art. 6(1)(f) | Legitimate interests as typical lawful basis for monitoring; requires balancing test |
| Art. 5(1)(c) | Data minimisation: collect only what is necessary for the monitoring purpose |
| Art. 5(1)(e) | Storage limitation: retain monitoring data only as long as necessary |
| Art. 12-14 | Transparency obligations: informing data subjects about monitoring |
| Art. 21 | Right to object to processing based on legitimate interests |
| Art. 22 | Automated decision-making restrictions applicable to behavioural analytics |
EDPB and National Authority Guidance
- EDPB Guidelines 3/2019 on Video Devices: Comprehensive guidance on CCTV use, including legal basis, transparency, retention, and access rights for video surveillance.
- EDPB WP248rev.01 Annex: National supervisory authority blacklists frequently include large-scale monitoring activities as mandatory DPIA triggers.
- ICO Employment Practices Code: UK guidance on workplace monitoring including CCTV, email, internet, and vehicle tracking.
- CNIL Guidance on Employee Monitoring (2023): French DPA requirements for workplace surveillance including keystroke logging, screen capture, and video monitoring.
Monitoring Scenarios
1. CCTV and Video Surveillance
Scope: Fixed and mobile cameras in public spaces, retail premises, transport hubs, workplaces. Key risks: Mass surveillance of individuals in publicly accessible areas; facial recognition enabling biometric identification; disproportionate retention creating behavioural profiles; function creep from security to performance monitoring. EDPB Guidelines 3/2019 requirements:
- Legitimate interest must be documented with a concrete, real, and present threat (not hypothetical security concerns).
- Signs must be placed at a reasonable distance indicating the area is under surveillance, the controller identity, the purpose, and where to find the full privacy notice.
- Retention should generally not exceed 72 hours unless justified by a specific incident.
- Facial recognition in public spaces requires explicit consent or substantial public interest legal basis.
2. Employee Monitoring
Scope: Email monitoring, internet usage logging, keystroke logging, screen recording, GPS tracking of company vehicles, badge access tracking. Key risks: Chilling effect on employee behaviour and communications; disproportionate intrusion into private life at work; monitoring of protected activities (trade union, whistleblowing); covert monitoring without transparency. Legal constraints:
- ECHR Article 8 (right to respect for private life) applies even in the workplace (Barbulescu v Romania, Grand Chamber, 2017).
- Employers must demonstrate monitoring is necessary, proportionate, and transparent.
- Works council or employee representative consultation may be required (varies by jurisdiction).
- Covert monitoring is permissible only in exceptional circumstances where there is reasonable suspicion of criminal activity or gross misconduct (Lopez Ribalda v Spain, Grand Chamber, 2019).
3. Location Tracking
Scope: GPS vehicle tracking, mobile device tracking, Wi-Fi positioning, Bluetooth beacons. Key risks: Continuous tracking creating comprehensive movement profiles; tracking extending beyond working hours; combination with other data revealing private activities; disproportionate monitoring intensity. Mitigation: Disable tracking outside working hours; use geofencing rather than continuous tracking; inform employees and obtain consent where required; provide option for personal use of vehicles with tracking disabled.
4. Internet and Communications Monitoring
Scope: Web browsing logs, email content scanning, instant messaging monitoring, social media monitoring. Key risks: Interception of private communications; monitoring of legally privileged communications; chilling effect on freedom of expression; access to special category data through content analysis. Legal constraints: ePrivacy Directive Article 5 (confidentiality of communications); national interception laws (e.g., UK Regulation of Investigatory Powers Act 2000, Investigatory Powers Act 2016).
5. Behavioural Analytics
Scope: Customer behaviour tracking in retail (heat mapping, dwell time), website analytics, social media sentiment analysis, predictive analytics for security. Key risks: Profiling without awareness; automated decision-making affecting individuals; combining data from multiple sources to create comprehensive profiles; targeting vulnerable individuals.
DPIA Methodology for Large-Scale Monitoring
Show full SKILL.md (502 more words)Show less
Phase 1: Monitoring Scope Definition (Week 1)
- Document the monitoring system: technology used, coverage area, data collected, retention period.
- Define the monitoring purpose precisely (security, safety, performance management, compliance, loss prevention).
- Identify all data subjects affected: employees, customers, visitors, bystanders, delivery personnel.
- Quantify the scale: number of individuals monitored, geographic coverage, hours of operation, data volume.
- Map data flows from collection through storage, access, analysis, and deletion.
Phase 2: Necessity and Proportionality Assessment (Week 2)
- Document the specific threat or business need justifying monitoring.
- Assess whether the purpose can be achieved without monitoring or with less intrusive monitoring.
- Evaluate alternative measures: physical security, access controls, procedural safeguards.
- Apply the EDPB balancing test: controller's legitimate interests vs data subject's rights, freedoms, and reasonable expectations.
- Consider temporal proportionality: is 24/7 monitoring necessary or would specific hours suffice?
- Consider spatial proportionality: can monitoring be limited to specific high-risk areas?
Phase 3: Data Subject Impact Assessment (Week 3)
- Assess impact on each data subject category (employees vs public vs visitors).
- Evaluate the reasonable expectations of data subjects in the monitored environment.
- Identify vulnerable groups affected (children, patients, job applicants).
- Assess the chilling effect on behaviour, communication, and freedom of movement.
- Document ECHR Article 8 balancing analysis for employee monitoring.
Phase 4: Technical and Organisational Safeguards (Week 4)
- Define access controls: who can view monitoring data, under what circumstances, with what authorisation.
- Set retention periods: default deletion schedule, exception process for incident-related retention.
- Implement transparency measures: signage, privacy notices, employee policies.
- Configure data protection by design: privacy masking, resolution reduction, automated deletion, purpose-bound access.
- Establish oversight: DPO review, audit schedule, complaint mechanism.
Phase 5: Documentation and Approval (Week 5)
- Document the DPIA per Art. 35(7) requirements.
- Record the DPO advice and whether it was followed.
- Obtain management sign-off with clear accountability for proportionality decisions.
- If residual risk remains high, initiate Art. 36 prior consultation with supervisory authority.
- Schedule periodic review (minimum annually; sooner if monitoring scope or technology changes).
Enforcement Precedents
- Greek DPA vs Municipality of Thessaloniki (2020): EUR 15,000 fine for CCTV monitoring in public spaces without DPIA and without adequate transparency measures (signage inadequate, no privacy notice accessible).
- Spanish AEPD vs Mercadona (2021): EUR 2.52 million fine for deploying facial recognition technology in supermarkets without adequate DPIA, proportionality assessment, or lawful basis.
- Belgian DPA vs Brussels Airport (2020): Reprimand for thermal camera surveillance during COVID-19 without DPIA for the new processing purpose.
- ICO vs Clearview AI (2022): GBP 7.5 million fine for processing biometric data of UK residents through facial recognition surveillance technology without lawful basis, transparency, or DPIA.
- CNIL vs Amazon France Logistique (2024): EUR 32 million fine for excessively intrusive employee monitoring system (scanner-based activity tracking with multiple indicators) violating proportionality and data minimisation principles.
- Romanian DPA vs Raiffeisen Bank (2020): EUR 150,000 fine for GPS tracking of employee vehicles without DPIA and extending beyond working hours.
© 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/pia-large-scale-monitor 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
Pia Large Scale Monitor 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 |
|---|---|---|---|---|---|---|
| Pia Large Scale Monitor this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~2.5k | 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 Pia Large Scale Monitor
What does Pia Large Scale Monitor do?
Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c). Pia Large Scale Monitor is an agent skill from mukul975/Privacy-Data-Protection-Skills. Conducts Privacy Impact Assessment for large-scale systematic monitoring under GDPR Article 35(3)(c).
When should I use Pia Large Scale Monitor?
Pia Large Scale Monitor fits situations like: tasks that involve Privacy and GDPR.
How do I install Pia Large Scale Monitor in Claude Code?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill pia-large-scale-monitor -a claude-code`. Or copy the skill folder (skills/privacy/pia-large-scale-monitor in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/pia-large-scale-monitor in your project. Claude Code loads it when a task matches its description.
How do I install Pia Large Scale Monitor in Codex?
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill pia-large-scale-monitor -a codex`. Or copy the skill folder (skills/privacy/pia-large-scale-monitor in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/pia-large-scale-monitor in your project. Codex loads it when a task matches its description.
Can I use Pia Large Scale Monitor 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 pia-large-scale-monitor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pia-large-scale-monitor, .gemini/skills/pia-large-scale-monitor, .github/skills/pia-large-scale-monitor and .opencode/skills/pia-large-scale-monitor in your project.
What does Pia Large Scale Monitor need to run?
Going by SKILL.md and its folder, Pia Large Scale Monitor needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Pia Large Scale Monitor 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 Pia Large Scale Monitor 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 Pia Large Scale Monitor use?
Pia Large Scale Monitor 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 Pia Large Scale Monitor use?
About 2.5k 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 1.8k tokens, read only when the agent opens those files.
What are the alternatives to Pia Large Scale Monitor?
Skills that share tags, products or a category with Pia Large Scale Monitor: 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 Pia Large Scale Monitor?
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.