Iso42001
Sushegaad/Claude-Skills-Governance-Risk-and-Compliance
Expert ISO 42001 AI Management System (AIMS) compliance advisor.
EU AI Act readiness assessment and sprint playbook. An agent skill from borghei/Claude-Skills.
Install AI Act Readiness
$ npx skills add borghei/Claude-Skills --skill ai-act-readiness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install borghei/Claude-Skills ai-act-readiness --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .claude/skills/ai-act-readiness && 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 "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .claude/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readinessType 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 borghei/Claude-Skills --skill ai-act-readiness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install borghei/Claude-Skills ai-act-readiness --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .agents/skills/ai-act-readiness && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .agents/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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 borghei/Claude-Skills --skill ai-act-readiness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install borghei/Claude-Skills ai-act-readiness --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .cursor/skills/ai-act-readiness && 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 "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .cursor/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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/borghei/Claude-Skills.git --path ra-qm-team/audit-prep/ai-act-readiness--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 borghei/Claude-Skills --skill ai-act-readiness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install borghei/Claude-Skills ai-act-readiness --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .gemini/skills/ai-act-readiness && 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 "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .gemini/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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 borghei/Claude-Skills ai-act-readinessInstalls 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 borghei/Claude-Skills --skill ai-act-readiness -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .github/skills/ai-act-readiness && 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 "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .github/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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 borghei/Claude-Skills --skill ai-act-readiness -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install borghei/Claude-Skills ai-act-readiness --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ra-qm-team/audit-prep/ai-act-readiness .opencode/skills/ai-act-readiness && 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 "ai-act-readiness" agent skill from https://github.com/borghei/Claude-Skills/tree/main/ra-qm-team/audit-prep/ai-act-readiness into .opencode/skills/ai-act-readiness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-act-readiness", 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
ai-act-readiness- GitHub stars
- 891
- Token cost
- ~1.8k tokens
- SKILL.md length
- 656 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 354
- Repo updated
- First seen
- Licence
- MIT
At a glance
EU AI Act readiness assessment and sprint playbook. An agent skill from borghei/Claude-Skills.
- Works in 4 steps: Run readiness score: python3… → Check GPAI obligations (if applicable):… → Pick sprint length based on score +… → …
- Preparing for the Aug 2026 high-risk AI system deadline
- SKILL.md covers When to use this skill, Key AI Act timelines, The readiness sprint and Critical AI Act areas, plus 6 more sections
- Runs Python scripts from its folder; calls python3
What it does
AI Act Readiness is an agent skill from borghei/Claude-Skills. EU AI Act readiness assessment and sprint playbook. Use when preparing for the Aug 2026 high-risk AI system deadline, when a notified-body conformity assessment is scheduled, or when GPAI (general-purpose AI) obligations apply.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/ai-act-readiness-checklist.md`, `references/high-risk-system-readiness-playbook.md` and `scripts/ai_act_readiness_score.py`).
It sits in Legal & Compliance, covering AI governance. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.
When your agent uses it
- Preparing for the Aug 2026 high-risk AI system deadline
- A notified-body conformity assessment is scheduled
- GPAI (general-purpose AI) obligations apply
Example prompts
- “/ai-act-readiness”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Run readiness score: python3 scripts/ai_act_readiness_score.py --config ai-system.yaml
- Check GPAI obligations (if applicable): python3 scripts/gpai_obligation_checker.py --model model.yaml
- Pick sprint length based on score + system risk class
- Execute sprint per references/ai-act-readiness-checklist.md
What it can do on your machine
Read from SKILL.md and the folder at commit 4a698e8. 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 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
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
AI Act Readiness loads about 1.8k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 656 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 borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 656 words, ~1,798 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-act-readiness/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- ai-act-readiness
- description
- EU AI Act readiness assessment and sprint playbook. Use when preparing for the Aug 2026 high-risk AI system deadline, when a notified-body conformity assessment is scheduled, or when GPAI (general-purpose AI) obligations apply.
- license
- MIT + Commons Clause
- metadata.version
- 1.0.0
- metadata.author
- borghei
- metadata.category
- compliance
- metadata.domain
- ra-qm-team
- metadata.updated
- 2026-05-27
- metadata.tags
- eu-ai-act, ai-readiness, high-risk-ai, gpai, conformity-assessment, compliance, ai-governance
EU AI Act Readiness
Operational playbook for EU AI Act compliance readiness — focused on the sprint to demonstrate readiness for the Aug 2026 high-risk AI deadline and ongoing conformity assessments.
When to use this skill vs. eu-ai-act-specialist:
- This skill: assessment imminent; need readiness sprint
- eu-ai-act-specialist: building AI Act compliance program; classifying systems; designing conformity processes
When to use this skill
| Situation | Skill applies |
|---|---|
| Aug 2026 high-risk deadline approaching | Yes — readiness sprint |
| Notified body conformity assessment scheduled | Yes — full prep |
| GPAI model obligations apply (Aug 2025+) | Yes — GPAI-specific checklist |
| Annual readiness review | Yes — periodic sprint |
| Building AI Act program from scratch | Use ra-qm-team/eu-ai-act-specialist |
| AI system classification | Use ra-qm-team/eu-ai-act-specialist |
Key AI Act timelines
| Date | Requirement |
|---|---|
| Aug 2, 2024 | AI Act enters into force |
| Feb 2, 2025 | Prohibited practices effective; AI literacy requirements |
| Aug 2, 2025 | GPAI provider obligations effective |
| Aug 2, 2026 | Most high-risk AI requirements effective |
| Aug 2, 2027 | All high-risk AI requirements + product safety harmonization |
The readiness sprint
8-week sprint (high-risk system, conformity assessment prep)
Week 1-2: System classification confirmation; gap analysis
Week 3-5: Documentation buildout (technical file, risk management, data governance)
Week 6-7: Conformity assessment internal dry-run
Week 8: External notified-body engagement / assessment4-week sprint (GPAI obligations)
Week 1: System classification (provider/deployer/importer/etc.)
Week 2: Documentation prep (model card, training data summary, copyright compliance)
Week 3: Risk assessment + transparency obligations
Week 4: Submission / publication of required informationCritical AI Act areas
Risk classification
Per Article 6 / Annex III, AI systems classify into risk categories:
| Category | Examples | Requirements |
|---|---|---|
| Prohibited | Social scoring; behavior manipulation of vulnerable groups | Cannot deploy |
| High-risk | Biometric ID; critical infrastructure; education; employment; access to essential services; law enforcement | Comprehensive obligations |
| Limited-risk (transparency) | Chatbots; deepfakes; emotion recognition | Disclosure obligation |
| Minimal-risk | Most enterprise AI; spam filters | Voluntary code of conduct |
| GPAI | Large language models; foundation models | Separate obligations (Article 51+) |
High-risk system requirements (Articles 9-15, plus 16-22)
| Requirement | Article |
|---|---|
| Risk management system | Art. 9 |
| Data governance + quality | Art. 10 |
| Technical documentation | Art. 11 |
| Record-keeping (logging) | Art. 12 |
| Transparency to users | Art. 13 |
| Human oversight | Art. 14 |
| Accuracy, robustness, cybersecurity | Art. 15 |
| Quality management system | Art. 17 |
| Conformity assessment | Art. 43 |
| Registration in EU database | Art. 71 |
| Post-market monitoring | Art. 72 |
| Serious incident reporting | Art. 73 |
GPAI provider obligations (Article 53+)
| Requirement | Detail |
|---|---|
| Technical documentation | Per Annex XI |
| Training data summary (public) | Sufficiently detailed |
| Copyright compliance | Honor opt-outs from text/data mining |
| Information to downstream providers | Enable downstream compliance |
| Code of practice compliance | (Optional but presumed conformity) |
GPAI with systemic risk (Article 55, models > 10^25 FLOPs training compute)
Additional requirements:
- Model evaluations
- Adversarial testing
- Systemic risk assessment + mitigation
- Serious incident reporting
- Cybersecurity protection
Show full SKILL.md (283 more words)Show less
Clarify First
Before running the readiness assessment, confirm these inputs. If any is unknown or vague, ASK — do not assume:
- AI system risk class — high-risk (Annex III), GPAI, or limited-risk (determines whether to run the 8-week high-risk sprint or the 4-week GPAI sprint, and which checklist applies)
- Trigger event — Aug 2026 high-risk deadline, scheduled notified-body conformity assessment, GPAI obligations, or annual review (sets sprint length and scope)
- Your role — provider, deployer, or importer (determines which obligation set is assessed)
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the assessment.
Quick start
- Run readiness score:
python3 scripts/ai_act_readiness_score.py --config ai-system.yaml - Check GPAI obligations (if applicable):
python3 scripts/gpai_obligation_checker.py --model model.yaml - Pick sprint length based on score + system risk class
- Execute sprint per references/ai-act-readiness-checklist.md
Common AI Act readiness failures
- Misclassification: deploying system as "limited-risk" when it's actually "high-risk" (Annex III)
- Risk management as one-time: AI Act requires continuous risk management
- Data governance gaps: training data without representativeness analysis
- Logging missing: post-market monitoring requires logs you don't have
- Human oversight theater: oversight that can't actually intervene
- GPAI training data summary missing: required since Aug 2025
- No conformity assessment plan: assuming notified body assessment is automatic
- AI literacy training skipped: required for staff working with AI systems
Tooling
| Script | Purpose |
|---|---|
scripts/ai_act_readiness_score.py | Score current AI Act readiness per system |
scripts/gpai_obligation_checker.py | Validate GPAI provider obligations (Article 53+) |
References
- ai-act-readiness-checklist.md — full punch list per requirement
- high-risk-system-readiness-playbook.md — high-risk-specific deep prep
Related skills
ra-qm-team/eu-ai-act-specialist— deep AI Act program managementra-qm-team/iso42001-ai-management— ISO 42001 AIMS (companion AI governance)ra-qm-team/audit-prep/aims-audit— AIMS audit-prep variantra-qm-team/audit-prep/gdpr-audit-prep— GDPR overlay for AI processing personal datara-qm-team/audit-prep/compliance-readiness— multi-framework readiness
© borghei, MIT. 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) in ra-qm-team/audit-prep/ai-act-readiness of borghei/Claude-Skills.
- SKILL.md
- references/ai-act-readiness-checklist.md
- references/high-risk-system-readiness-playbook.md
- scripts/ai_act_readiness_score.py
- scripts/gpai_obligation_checker.py
Open the folder on GitHubat commit 4a698e8
Compare with similar skills
AI Act Readiness 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 |
|---|---|---|---|---|---|---|
| AI Act Readiness this skillborghei/Claude-Skills | 891 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Iso42001Sushegaad/Claude-Skills-Governance-Risk-and-Compliance | 946 | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| AI Risk Managementbriiirussell/cybersecurity-skills | 413 | — | ~3.7k | Automated safety check: Notes | MIT | |
| EU AI Act System Inventoryanthropics/claude-for-legal | 9.6k | 3 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Eu AI Act Readinessseb1n/awesome-ai-agent-skills | 206 | — | ~3.3k | Automated safety check: Pass | MIT | |
| AI GovernanceHack23/cia | 239 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 |
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Questions about AI Act Readiness
What does AI Act Readiness do?
EU AI Act readiness assessment and sprint playbook. An agent skill from borghei/Claude-Skills. AI Act Readiness is an agent skill from borghei/Claude-Skills. EU AI Act readiness assessment and sprint playbook.
When should I use AI Act Readiness?
AI Act Readiness fits situations like: preparing for the Aug 2026 high-risk AI system deadline; A notified-body conformity assessment is scheduled; GPAI (general-purpose AI) obligations apply.
How do I install AI Act Readiness in Claude Code?
Run `npx skills add borghei/Claude-Skills --skill ai-act-readiness -a claude-code`. Or copy the skill folder (ra-qm-team/audit-prep/ai-act-readiness in borghei/Claude-Skills) into .claude/skills/ai-act-readiness in your project. Claude Code loads it when a task matches its description.
How do I install AI Act Readiness in Codex?
Run `npx skills add borghei/Claude-Skills --skill ai-act-readiness -a codex`. Or copy the skill folder (ra-qm-team/audit-prep/ai-act-readiness in borghei/Claude-Skills) into .agents/skills/ai-act-readiness in your project. Codex loads it when a task matches its description.
Can I use AI Act Readiness 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 borghei/Claude-Skills --skill ai-act-readiness -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-act-readiness, .gemini/skills/ai-act-readiness, .github/skills/ai-act-readiness and .opencode/skills/ai-act-readiness in your project.
What does AI Act Readiness need to run?
Going by SKILL.md and its folder, AI Act Readiness needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does AI Act Readiness 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 AI Act Readiness 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 AI Act Readiness use?
AI Act Readiness is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Act Readiness use?
About 1.8k tokens (SKILL.md is roughly 7.2k 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 4.3k tokens, read only when the agent opens those files.
What are the alternatives to AI Act Readiness?
Skills that share tags, products or a category with AI Act Readiness: Iso42001 (Sushegaad/Claude-Skills-Governance-Risk-and-Compliance, 946 stars), AI Risk Management (briiirussell/cybersecurity-skills, 413 stars), EU AI Act System Inventory (anthropics/claude-for-legal, 9.6k stars) and Eu AI Act Readiness (seb1n/awesome-ai-agent-skills, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Act Readiness?
borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 891 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.
Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.