adequacy-assessment

adequacy-assessment is a skill for Claude Code, Codex from onfire7777/universal-ai-skills-library. It costs 72 tokens per session (2,050 once invoked), scanned A, a copy of adequacy-assessment, MIT.

Guidance for assessing whether a country or territory provides enough privacy protection for transferring personal data under Article 45 of the GDPR, the European Union's data protection law. It covers European Commission adequacy decisions, including cases where protection applies only to certain sectors.

In plain words
What is it for?
Use it to check adequacy coverage, assess third-country transfers, handle partial decisions, and review whether an adequacy decision remains relevant.
Why use it?
It helps determine whether a data transfer can rely on an adequacy decision or needs another legal safeguard. This avoids treating a country-wide decision as broader than it really is.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to check adequacy coverage, assess third-country transfers, handle partial decisions, and review whether an adequacy decision remains relevant.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/onfire7777/universal-ai-skills-library/adequacy-assessment
Install

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.

Any agent
npx skills add onfire7777/universal-ai-skills-library --skill adequacy-assessment
Clone the repo
git clone --depth 1 https://github.com/onfire7777/universal-ai-skills-library

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for adequacy-assessment

README.md
[![agentmods](https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/adequacy-assessment/github.svg)](https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/adequacy-assessment)
Your own site
<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/adequacy-assessment"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/adequacy-assessment/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.

agentmods 80×15 button for adequacy-assessment

Your own site · 80×15
<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/adequacy-assessment"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/adequacy-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 98% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.02050
Opus 5 $0.00036 $0.01025
Sonnet 5 $0.00014 $0.00410
Haiku 4.5 $0.00007 $0.00205

Measured 13d ago against content hash b6ec9c678fad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

adequacy-assessment 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 13d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

98% identical to adequacy-assessment — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/adequacy-assessment/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assessing Third-Country Adequacy

Overview

GDPR Article 45 provides that the European Commission may determine that a third country, a territory, or one or more specified sectors within a third country, or an international organisation ensures an adequate level of protection for personal data. Where such an adequacy decision exists, transfers of personal data to the covered country, territory, or sector may take place without any specific authorisation or additional safeguard requirement. This skill guides the assessment of existing adequacy decisions and the handling of partial adequacy coverage.

Current EC Adequacy Decisions

As of March 2026, the European Commission has adopted adequacy decisions for the following countries and territories:

Country/Territory Decision Reference Date Adopted Scope Periodic Review
Andorra Decision 2010/625/EU 19 October 2010 Full country Ongoing monitoring
Argentina Decision 2003/490/EC 30 June 2003 Full country Ongoing monitoring
Canada Decision 2002/2/EC 20 December 2001 Commercial organisations subject to PIPEDA only Ongoing monitoring
Faroe Islands Decision 2010/146/EU 5 March 2010 Full territory Ongoing monitoring
Guernsey Decision 2003/821/EC 21 November 2003 Full territory Ongoing monitoring
Israel Decision 2011/61/EU 31 January 2011 Full country Ongoing monitoring
Isle of Man Decision 2004/411/EC 28 April 2004 Full territory Ongoing monitoring
Japan Decision (EU) 2019/419 23 January 2019 Commercial sector subject to APPI supplementary rules Biennial review; first review completed January 2021; second review 2023
Jersey Decision 2008/393/EC 8 May 2008 Full territory Ongoing monitoring
New Zealand Decision 2013/65/EU 19 December 2012 Full country Ongoing monitoring
South Korea Decision (EU) 2022/254 17 December 2021 (effective 2022) Commercial and public sector subject to PIPA Biennial review
Switzerland Decision 2000/518/EC 26 July 2000 Full country Ongoing monitoring; assessed under revised FADP effective 1 September 2023
United Kingdom Decision (EU) 2021/1772 28 June 2021 Full country Sunset clause: expires 27 June 2025 unless renewed; renewal assessment underway
Uruguay Decision 2012/484/EU 21 August 2012 Full country Ongoing monitoring
United States (DPF) Decision (EU) 2023/1795 10 July 2023 Self-certified organisations under the EU-US DPF only Annual review; first review October 2024

Read the full file on GitHub · 139 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 13d ago First seen · 139 lines · 72 tokens per session scan A b6ec9c678fad

Subscribe to this mod's changes

adequacy-assessment is a skill published in the GitHub repository onfire7777/universal-ai-skills-library (16 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 2,050 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to adequacy-assessment, differing in 19 lines, and is treated as a copy.

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