anthropics/claude-for-legal1 file

Vendor AI Review

>

Specification
Skill ID
anthropics/claude-for-legal/vendor-ai-review
Publisher
anthropics
Repository
claude-for-legal
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

anthropics/claude-for-legal/vendor-ai-reviewInstalls these files
  • SKILL.md

What this skill tells the agent

/vendor-ai-review

  1. Read ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md. Confirm vendor governance positions are populated — if not, stop and direct to setup.
  2. Use the framework below.
  3. Confirm document type (AI addendum / main agreement AI provisions / ToS). If only an AUP was provided, ask for the full terms.
  4. Term-by-term review: training on data, confidentiality of inputs, model changes, output IP, liability, incident notification, human review rights, use restrictions, audit rights.
  5. AI addendum gap check if DPA exists but no AI addendum.
  6. AI policy consistency diff vs. ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md.
  7. Output: bottom line, term-by-term, recommended redlines, if-they-won't-move routing.
/ai-governance-legal:vendor-ai-review openai-enterprise-agreement.pdf

Matter context

Matter context. Check ## Matter workspaces in the practice-level CLAUDE.md. If Enabled is ✗ (the default for in-house users), skip the rest of this paragraph — skills use practice-level context and the matter machinery is invisible. If enabled and there is no active matter, ask: "Which matter is this for? Run /ai-governance-legal:matter-workspace switch <slug> or say practice-level." Load the active matter's matter.md for matter-specific context and overrides. Write outputs to the matter folder at ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/matters/<matter-slug>/. Never read another matter's files unless Cross-matter context is on.


Purpose

Vendor AI terms are where your governance positions actually get tested. The cold-start interview captures what you want. This skill checks what you agreed to — and flags the gaps between those two things.

The direction here is always the same: we are the deployer or buyer reviewing the vendor's terms. This is the opposite posture from the DPA review controller/processor question — there's no flip.

What varies is the input:

  • A standalone AI agreement or AI addendum (most structured)
  • A vendor's universal terms of service with AI provisions embedded (often buried)
  • An acceptable use policy (tells you what you can't do; says nothing about what the vendor can do with your data or outputs)
  • A combination — master agreement + DPA + AI addendum (common for serious enterprise AI vendors)

When there's a DPA already in place, this review complements it — it's not a substitute. The DPA governs data protection obligations; the AI terms govern model-specific rights and risks. Both need to be reviewed.


Load the playbook

Read ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md → ## Vendor AI governance. Also read ## AI policy commitments — vendor terms can't be consistent with a use restriction our own policy imposes if we've agreed to something different.

If ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md contains [PLACEHOLDER], surface this bounce:

I notice you haven't configured your practice profile yet — that's how I tailor vendor governance positions to your practice. Two choices: - Run /ai-governance-legal:cold-start-interview (2 minutes) to configure your profile, then I'll review tailored to YOUR positions. - Say "provisional" and I'll review against generic defaults — US jurisdiction, middle risk appetite, lawyer role, no playbook — and tag every output [PROVISIONAL — configure your profile for tailored output] so you can see what I do before committing.

Provisional mode

If the user says "provisional," run the vendor AI review normally using these generic defaults: middle risk appetite, lawyer role, US jurisdiction, no playbook (flag all common vendor-AI risks from first principles rather than matching to configured positions). Tag the reviewer note and every finding block with [PROVISIONAL]. At the end of the output, append:

"That was a generic run against default assumptions. Run /ai-governance-legal:cold-start-interview to get output calibrated to YOUR practice — your vendor governance positions, your jurisdiction, your risk appetite. 2 minutes."

Before reading the document

If the user hasn't shared the actual vendor terms, ask:

"Can you share the vendor's AI terms? The most useful thing is the actual contract language — the AI addendum if there is one, or the main agreement with AI provisions highlighted. An acceptable use policy alone won't tell us what the vendor can do with our inputs; it only tells us what we're allowed to do."

If they share an acceptable use policy only:

"This is the acceptable use policy — it tells us what we can't do with the vendor's AI. That's useful context, but it doesn't address the commercial terms: whether the vendor can train on our data, what their liability is for AI errors, whether they notify us when the model changes. Do you have the service agreement or AI addendum?"

The term-by-term review

Core AI-specific terms (check every vendor AI agreement)

Review each term below. For each, extract what the vendor's contract actually says and compare it against the position in ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md → ## Vendor AI governance (standard / acceptable fallback / automatic no). The default positions come from the team's playbook, not from this skill.

TermWhat to look for
Training on our dataDoes the vendor use our inputs to train, fine-tune, or improve models? Is there an explicit opt-out or prohibition? Is training opt-in or opt-out by default?
Confidentiality of inputsAre our prompts, documents, and data confidential? Any "quality review" or human-review carveouts that would let vendor staff read inputs?
Model changesAny notice obligation for material changes to the model? Version pinning available?
Output ownership / IPWho owns AI-generated content? Any license-back to the vendor on outputs? Any IP indemnity?
Liability for outputsDoes the vendor accept any liability if the AI produces harmful, incorrect, or infringing outputs? Cap structure? Carve-outs?
Incident notificationHow and when are we notified if the AI system fails, is compromised, or produces systematic errors affecting us?
Human review rightsCan we require human review of outputs in specific cases? Can we appeal or dispute an AI decision?
Use restrictionsWhat are we prohibited from doing? Does it match what we actually want to use the tool for? Any definitional terms (e.g., "automated decision-making") that could sweep in our intended uses?
Audit / auditabilitySOC 2, third-party audits, bias testing results — any audit rights?
Subprocessors / model providersDoes the vendor use sub-vendors for the model? Are they disclosed? Whose terms govern?
Data residencyWhere is our data processed? Where does it go for inference?
Term and terminationWhat happens to our data when we terminate? Deletion timelines?

Use this skill in a project

Open any RiverX project, search the Skills panel for anthropics/claude-for-legal/vendor-ai-review, and install it in one click.

Use this skill