Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add personamanagmentlayer/pcl --skill gdpr-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/personamanagmentlayer/pcl/gdpr-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/gdpr-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/gdpr-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/gdpr-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/gdpr-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 255 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 378 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.02770 |
| Opus 5 | $0.00036 | $0.01385 |
| Sonnet 5 | $0.00014 | $0.00554 |
| Haiku 4.5 | $0.00007 | $0.00277 |
Grade A, and why
gdpr-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Expert
You are an expert in GDPR (General Data Protection Regulation) compliance, specializing in data protection, privacy by design, consent management, data subject rights, and DPO responsibilities.
Core Concepts
GDPR Fundamentals
- Lawful Basis: Legal grounds for processing data
- Data Subject Rights: Access, rectification, erasure, portability
- Consent Management: Explicit, informed, freely given
- Data Minimization: Collect only necessary data
- Purpose Limitation: Use data only for stated purposes
- Accountability: Demonstrate compliance
Key Principles (Article 5)
- Lawfulness, Fairness, Transparency: Clear processing
- Purpose Limitation: Specific, explicit purposes
- Data Minimization: Adequate, relevant, limited
- Accuracy: Kept up to date
- Storage Limitation: Retained only as needed
- Integrity and Confidentiality: Secure processing
- Accountability: Controller responsibility
Data Subject Rights
- Right to Access (Article 15): Obtain copy of data
- Right to Rectification (Article 16): Correct inaccurate data
- Right to Erasure (Article 17): "Right to be forgotten"
- Right to Restriction (Article 18): Limit processing
- Right to Portability (Article 20): Transfer data
- Right to Object (Article 21): Object to processing
- Automated Decisions (Article 22): Human intervention
Privacy by Design
- Data Protection by Default: Maximum privacy settings
- Pseudonymization: Separate identity from data
- Encryption: Protect data at rest and in transit
- Access Controls: Role-based permissions
- Privacy Impact Assessments: Risk evaluation
- Data Protection Officers: Oversight and compliance
Code Examples
Consent Management System
# consent_management.py - GDPR-compliant consent tracking
from datetime import datetime, timedelta
from enum import Enum
import json
class ConsentPurpose(Enum):
MARKETING = "marketing"
ANALYTICS = "analytics"
PERSONALIZATION = "personalization"
ESSENTIAL = "essential"
class ConsentManager:
def __init__(self):
self.consents = {}
def record_consent(self, user_id, purpose, metadata):
"""Record user consent with full audit trail."""
consent_record = {
'user_id': user_id,
'purpose': purpose.value,
'status': 'given',
'timestamp': datetime.now().isoformat(),
'expires_at': (datetime.now() + timedelta(days=730)).isoformat(),
'version': '1.0',
'metadata': metadata
}
if user_id not in self.consents:
self.consents[user_id] = {}
self.consents[user_id][purpose.value] = consent_record
self._audit_log('consent_given', consent_record)
return consent_record
def withdraw_consent(self, user_id, purpose):
"""Allow users to withdraw consent easily."""
if user_id in self.consents and purpose.value in self.consents[user_id]:
self.consents[user_id][purpose.value]['status'] = 'withdrawn'
self.consents[user_id][purpose.value]['withdrawn_at'] = datetime.now().isoformat()
self._audit_log('consent_withdrawn', self.consents[user_id][purpose.value])
return True
return False
def check_consent(self, user_id, purpose):
"""Verify valid consent before processing."""
if user_id not in self.consents or purpose.value not in self.consents[user_id]:
return False
consent = self.consents[user_id][purpose.value]
if consent['status'] != 'given':
return False
# Check expiration
expires_at = datetime.fromisoformat(consent['expires_at'])
if datetime.now() > expires_at:
return False
return True
def _audit_log(self, action, record):
"""Maintain audit trail as required by GDPR."""
print(f"GDPR Audit: {action} - {json.dumps(record)}")
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 392 lines · 71 tokens per session scan A fc3083199251
gdpr-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed today), licensed Apache-2.0. It adds 71 tokens to every session and 2,770 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
implementing-gdpr-data-protection-controls
The General Data Protection Regulation (EU) 2016/679 (GDPR) is the EU's comprehensive data protection law governing the collection, processing, storage, and transfer of personal data. This skill cover.
GDPR Compliance Testing
Testing GDPR compliance requirements including data deletion, consent management, data portability, right to erasure, and privacy policy enforcement.
implementing-gdpr-data-protection-controls
The General Data Protection Regulation (EU) 2016/679 (GDPR) is the EU's comprehensive data protection law governing the collection, processing, storage, and transfer of personal data. This skill cover.
implementing-gdpr-data-protection-controls
The General Data Protection Regulation (EU) 2016/679 (GDPR) is the EU's comprehensive data protection law governing the collection, processing, storage, and transfer of personal data. This skill cover.
gdpr-privacy
Use when producing the GDPR artifacts a product publishes or hands over: a privacy policy true to what it processes, a cookie/consent banner, a lawful basis per purpose, an Art. 28 DPA, an SCC transfer mechanism, or a DSAR flow. Drafts for counsel review. NOT internal retention rules (that is data-policy), NOT…
gdpr-data-handling-note
Drafts a plain-language data handling notice for a journalistic or media production project that involves collecting, storing, or processing personal data — structured to meet GDPR transparency requirements while remaining understandable to non-lawyers.