EU AI Act per-system inventory — track each AI system's role (provider, deployer, importer, distributor, authorized representative, product manufacturer) and risk tier (prohibited, high-risk, limited, minimal, GPAI, GPAI+systemic). Role and tier are assessed per system, not per company. Use when the user says "ai inventory", "add an ai system", "what systems do we have", "classify this ai system", "eu ai act register", or "ai system registry".
EU AI Act per-system inventory — track each AI system's role (provider, deployer, importer, distributor, authorized representative, product manufacturer) and risk tier (prohibited, high-risk, limited, minimal, GPAI, GPAI+systemic). Role and tier are assessed per system, not per company. Use when the user says "ai inventory", "add an ai system", "what systems do we have", "classify this ai system", "eu ai act register", or "ai system registry".
Codex v1 local-input note: This migrated skill supports local files and pasted text by default. References to Drive, CLM IDs, Slack, Westlaw, iManage, Ironclad, eDiscovery, dockets, or other remote systems require a separately configured Codex connector/MCP server. When a connector is unavailable, ask for a local export, local file path, or pasted excerpts. If config/local/codex-for-legal/<practice>/CLAUDE.md is missing, ask the user to run the relevant cold-start-interview or customize skill and copy from config/templates/codex-for-legal/<practice>/CLAUDE.md.
$ai-governance-legal:ai-inventory
When this runs
The user wants to manage their AI system inventory under the EU AI Act. The
core idea the skill exists to enforce: role and tier are per-system, not
per-company. A single organization can be a provider of System A, a
deployer of System B, and an importer of System C. Each combination
triggers a different set of obligations under the AI Act. The inventory
exists so those assessments are tracked where you can find them — the
obligations themselves are derived in conversation, not from a table.
What to do
Read the config. Read
config/local/codex-for-legal/ai-governance-legal/CLAUDE.md.
If it doesn't exist or still has [PLACEHOLDER] markers, direct the user
to $ai-governance-legal:cold-start-interview first.
Read the inventory. Inventory lives at
config/local/codex-for-legal/ai-governance-legal/ai-systems.yaml.
If it doesn't exist, create it with an empty systems: list when the
first add runs.
Dispatch on the argument:
No argument, or list → show the inventory table (see List below).
add → run the Add flow.
edit <id> → show the current record, ask what to change, update one
field, confirm, write.
classify <id> → run the Classification walk-through on an
existing record, updating role, tier, role_basis, and tier_basis.
show <id> → show the full record.
On list, offer the dashboard:
"Want the full dashboard? Filter by status / tier / EU nexus / owner.
Say the word."
Close every action with a hook into the lawyer's work.
After any write, say:
Recorded. When you're ready to walk through obligations for this
system, just ask — I'll do it in-conversation and flag where the AI
Act article mapping needs your verification. I don't derive
obligations from a table because the mapping is complex and changing.
List format
Render as a compact table:
ID
Name
Owner
Status
EU nexus
Role
Tier
Next review
sys-001
Resume screening
HR / Jamie
in_production
yes
deployer
high_risk
2026-08-01
sys-002
Email drafting assistant
IT / Priya
in_production
no
deployer
limited
2026-12-01
Under the table, show counts by tier and a line: "N systems flagged for
review within 30 days."
Add flow (interview)
Ask, one field at a time (or accept a paste). The required fields are
name, owner, description, status, eu_nexus. The rest can be
deferred — say so explicitly: "you can come back to classification with
$ai-governance-legal:ai-inventory classify <id>."
Name. Short label for the system.
Owner. Person or team accountable for it day-to-day.
Description. One or two sentences. What does it do, and against
what data?
EU nexus. Is the system deployed in the EU/EEA, offered to users in
the EU/EEA, or used to produce outputs that affect people in the
EU/EEA? If any of these are true, EU AI Act analysis applies.
Proceed to classification? Offer to run the walk-through now, or
skip and come back later.
Assign an ID: sys-NNN where NNN is the next integer in the file.
Classification walk-through
The walk-through produces role, role_basis, tier, tier_basis. Both
bases are tagged [verify against current AI Act text] — not because the
skill is hedging, but because the article mapping is complex and the AI
Act is still phasing in. The lawyer owns verification.
Step 1: Role
Who does what to this system?
Options, with the distinguishing test:
Provider — you develop it (or have it developed) and place it on the
EU market or put it into service under your own name or trademark.
Deployer — you use it under your own authority, not for personal
non-professional use. (Most common inside companies.)
Importer — you bring an AI system into the EU from a provider
established outside the EU.
Distributor — you make an AI system available on the EU market
without being the provider or importer.
Authorized representative — you act on behalf of a non-EU provider
and are established in the EU.
Product manufacturer — you put a general-purpose AI system (or
another AI system) into a product under your own name/trademark. Treated
as provider for the product.
Dual-role flag. If the user substantially modifies a vendor system
(fine-tunes on their own data, changes the intended purpose, rebrands),
they may become a provider of the modified system even if they started
as a deployer. Call this out when they describe any modification beyond
configuration. [verify against current AI Act text — Article 25, provider obligations and substantial modification]
Write the role. Write role_basis in one sentence.
Step 2: Tier
What does the system do, and does the use case fall into a regulated
category?
Check in order:
A. Article 5 prohibited practices.[verify against current AI Act text — Article 5]
Summaries, not definitive text:
Subliminal or deceptive techniques materially distorting behavior
Exploiting vulnerabilities (age, disability, socio-economic status) to
materially distort behavior
Social scoring by public authorities leading to detrimental treatment
Real-time remote biometric ID in publicly accessible spaces for law
enforcement (narrow exceptions)
Biometric categorization inferring race, political opinions, union
membership, religious or philosophical beliefs, sex life, or sexual
orientation
Emotion recognition in the workplace or education (medical and safety
exceptions)
Facial image database scraping from the internet or CCTV
Predictive policing based solely on personality traits
If matched → tier is prohibited. Flag the use case as stop and route to
the governance team's prohibited-practice workflow.
B. Annex III high-risk areas.[verify against current AI Act text — Annex III]
Summaries:
Biometric identification and categorization
Critical infrastructure (digital infrastructure, road traffic, supply of
water / gas / heating / electricity)
Education and vocational training (access, evaluation, proctoring,
monitoring prohibited behavior)
Essential private and public services (public benefits, credit scoring
for individuals, risk assessment and pricing for life/health insurance,
emergency dispatch)
Law enforcement (risk assessment, polygraphs, deepfake detection,
reliability of evidence, profiling)
Migration, asylum, border control (risk assessment, travel document
verification, examination of applications)
Administration of justice and democratic processes (research and
interpretation, influencing elections)
If matched → tier is high_risk. Note the Annex III area and subsection.
C. GPAI.[verify against current AI Act text — Article 51 and surrounding]
GPAI: model trained on broad data at scale, designed for generality,
capable of competently performing a wide range of distinct tasks.
GPAI + systemic risk: cumulative compute > 10^25 FLOPs, or designated
by the Commission.
D. Limited risk. Chatbots interacting with natural persons, deepfakes,
emotion recognition and biometric categorization systems outside Article 5
scope — transparency obligations apply.
E. Minimal risk. Everything else.
Write the tier. Write tier_basis in one sentence, citing the article or
Annex entry that matched, tagged [verify against current AI Act text].
Step 3: Recommendations
Offer three next steps:
"Want me to walk through obligations for this system? I'll do it in
conversation — I don't derive them from a table."
"Want to run $ai-governance-legal:aia-generation to produce a full
impact assessment?"
"Want to set a next review date? I'll add it to the inventory."
Record format
systems:-id:sys-001name:"Resume screening tool"owner:"HR / Jamie"description:"Filters inbound CVs against job criteria"status:in_production# planned | in_development | in_production | deprecatedeu_nexus:true# deployed, offered, or affects people in the EU/EEArole:deployer# provider | deployer | importer | distributor | authorized_rep | product_manufacturerrole_basis:"We license from VendorX and deploy internally [verify against current AI Act text]"tier:high_risk# prohibited | high_risk | limited | minimal | gpai | gpai_systemictier_basis:"Annex III(4)(a) — employment, recruitment selection [verify against current AI Act text]"obligations_assessed:falseobligations_note:"To assess: as deployer of a high-risk system — human oversight, input data quality, monitoring, record-keeping, informing workers, FRIA if public body/service — see Article 26 [verify against current AI Act text]"next_review:"2026-08-01"review_trigger:"on substantial modification or annually"created:"2026-05-11"updated:"2026-05-11"
Why this skill does NOT auto-derive obligations
The inventory stores role, tier, and the basis for each. It does NOT
contain a hardcoded role × tier → obligations table.
When the user asks "what are my obligations for System X?", the skill
does the analysis in conversation, tagged [verify], and routes to
$ai-governance-legal:aia-generation for the formal impact assessment
if needed.
This is deliberate:
Article mapping is complex and the AI Act is phasing in through 2027.
Confident-and-wrong on a compliance obligation ends up in a board memo.
The inventory is a registry for the lawyer. The lawyer owns the
obligation analysis.
Guardrails
Never classify silently. The classification walk-through must be
visible; do not auto-classify from a system description.
[verify] tags stay. They are not hedging — they are the point.
Do not strip them in outputs.
Flag substantial modification. Whenever a system is modified beyond
configuration, prompt the user to re-run $ai-governance-legal:ai-inventory classify —
modification can change role.
Don't declare obligations from a table. If asked, do the analysis
in conversation and route to $ai-governance-legal:aia-generation for anything that needs
a formal record.
