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eu-ai-act-specialist

EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and deadlines? Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations. Cites Articles + Annexes for every output. NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute.

68

Quality

85%

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SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured operational core: executable commands backed by real bundled scripts, clearly sequenced workflows with a dedicated pre-deployment validation checklist, and exemplary progressive disclosure into verified one-level-deep references. Its main weakness is redundancy — repeated decision statements, triple-listed tool commands, and a keyword-stuffing block that inflate tokens without adding guidance.

Suggestions

Collapse the tool-command listings: keep them in Quick Start and have Core Responsibilities and Workflows reference the tool by name, cutting roughly 15-20% of body tokens.

Replace the flat Keywords section with a short line noting the description already carries trigger terms, or move the keyword list into a reference file — it is discovery padding, not operational content.

Add one example systems.json input snippet (or point to the script's embedded sample by flag) so a user can construct valid input without opening the script source.

DimensionReasoningScore

Conciseness

The body is dense with genuinely non-obvious regulatory detail, but it repeats itself: the three decisions are stated in the intro and restated in Core Responsibilities, every tool command appears in both Quick Start and Core Responsibilities (and again in Workflows), and the ~60-term Keywords block is SEO-style padding that adds tokens without operational value. This matches the level-3 anchor ('mostly efficient but includes some unnecessary explanation or could be tightened'); it is not level 4 because the triple repetition of commands and the keyword block are clearly trimmable, and not level 2 because the core content is domain-specific rather than explanations of things Claude already knows.

3 / 5

Actionability

Quick Start gives copy-paste-ready commands ('python scripts/ai_system_risk_classifier.py path/to/systems.json') for all three tools, each with a documented no-arg embedded sample, and all three scripts exist in the bundle with real main entry points. Role/Article tables, the Annex IV artifact checklist, and the concrete Output Standards template make guidance executable. It stops short of level 5 because the input JSON schema is never shown in the body — the user must open the scripts or infer the format — leaving minor gaps.

4 / 5

Workflow Clarity

Workflows 1-4 are clearly sequenced with numbered steps, conditional branching ('If high-risk: run planner'), and Workflow 3 is itself an explicit pre-launch validation checklist with per-item confirmations. This matches the level-4 anchor (clear sequence with most checkpoints present, minor validation gaps). It is not level 5 because no workflow includes an explicit fix-and-retry feedback loop (e.g., what to do when classification is disputed or the planner flags missing Annex IV items), and several Workflow 2 steps are unactionable comments ('# 2. Assemble: ...') rather than commands; it is above level 3 because the destructive/batch validation cap does not apply — these are analytical and documentation workflows, and Workflow 3 supplies the verification gate.

4 / 5

Progressive Disclosure

Verified against the actual bundle: all four references/ files and all three scripts/ files referenced in the body exist, each Core Responsibility section ends with a targeted pointer ('See references/eu_ai_act_titles.md for the full Article-by-Article walkthrough'), and a consolidated, annotated References section lists every file with its scope. Reference files cross-link only laterally within the same level (no 2+ level nesting), and deep regulatory detail is correctly split out of the overview. This matches the level-5 anchor (clear overview with well-signaled one-level-deep references, content appropriately split, easy navigation).

5 / 5

Total

16

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it defines a precise niche, enumerates three concrete decisions with Article-level specificity, gives explicit usage triggers, and includes negative boundaries against adjacent skills. The only meaningful gap is keyword coverage — a few natural synonym phrasings (GPAI, CE marking, 'AI regulation Europe') that users might say are missing from the description itself.

Suggestions

Add one or two high-frequency natural phrasings users actually say, e.g. 'GPAI / general-purpose AI model obligations' and 'CE marking for AI systems', to the description to close the trigger-term gap.

Consider a brief 'NOT GDPR' clause in the description (it currently appears only in the body) since GDPR is the most likely wrong-skill collision for AI compliance queries.

DimensionReasoningScore

Specificity

The description enumerates three concrete, comprehensive decisions with regulatory precision: risk-tier classification ("prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk"), the Article 43 conformity route ("Module A internal control vs Module H full QMS + notified body") plus Annex IV documentation, and per-role obligations with deadlines, and states the concrete output property "Cites Articles + Annexes for every output". This matches the level-5 anchor (multiple specific concrete actions, comprehensive coverage); level 4 requires 'minor gaps in coverage' and none are evident.

5 / 5

Completeness

Explicitly answers 'what' (three enumerated Article-level decisions with named deliverables) and 'when' ("Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations") with concrete trigger phrases, exactly matching the level-5 anchor. It is not level 4 because the 'when' clause is specific and trigger-anchored rather than merely present.

5 / 5

Trigger Term Quality

Includes the dominant natural terms a compliance user would say — "EU AI Act", "Regulation (EU) 2024/1689", "high-risk", "conformity assessment", "deployer obligations" — plus explicit trigger contexts ("Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations"). It falls short of the level-5 anchor because several natural synonyms users actually say ("AI regulation Europe", "GPAI", "CE marking AI", "notified body" as a standalone query term) are absent, matching the level-4 anchor 'good keyword coverage; a few natural terms missing'.

4 / 5

Distinctiveness Conflict Risk

The skill occupies a clear niche (EU AI Act operational compliance for compliance teams) and actively disambiguates with explicit negative boundaries — "NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute" — minimizing wrong-skill triggering. This matches the level-5 anchor (clear niche with distinct triggers, minimal conflict risk); level 4 would require some residual overlap risk with closely related skills, which the NOT-clauses already guard against.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

alirezarezvani/claude-skills

Path

ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/SKILL.md

Reviewed

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