Claude Contract Review Prompt: Internal Issue-Spotting Workflow

What is a safe use of an AI prompt for contract review?

Internal contract issue-spotting workflow for authorized teams: materials, issue log, escalation, and qualified human review.
Internal Contract Issue-Spotting Workflow

A safe AI contract-review prompt helps an authorized team organize visible clause text against its own approved playbook, create an issue log, and prepare questions for qualified counsel. It does not determine enforceability, replace legal judgment, approve terms, or create a redline that should be relied on without attorney review.

Important legal limitation: Contract obligations, risk positions, and enforceability depend on the parties, jurisdiction, governing law, and facts. This workflow is for internal issue spotting and draft organization only; it is not legal advice. Have qualified counsel review any agreement, negotiation position, or redline before reliance.

Decide whether the document is suitable for AI-assisted issue spotting

Proceed only ifEscalate before using an AI tool if
You are authorized to handle the document and to use the selected AI environment for it.The document contains regulated, privileged, highly confidential, personal, or third-party data without a documented approval path.
An approved playbook, fallback positions, and escalation contacts exist.The agreement is governed by an unfamiliar jurisdiction, involves litigation, employment, securities, privacy, public-sector, or other specialist issues.
A qualified reviewer will make the final decision.The output is being used as a substitute for attorney review or to send a counterparty a final redline.

Prepare the review packet before prompting

Do not ask a model to “find every legal risk” without a decision standard. Prepare the exact contract version, approved clause playbook, business context, deal value, acceptable fallback positions, unresolved commercial decisions, and a named reviewer. Remove or minimize data that is not needed for the review and follow your organization’s approved AI, privacy, retention, and confidentiality rules.

Copy-ready prompt: issue log against an approved playbook

ROLE
You are an internal contract-review assistant. You organize clause-level issues for review by qualified counsel; you do not provide legal advice or final negotiation positions.

AUTHORIZED MATERIALS
- Agreement type and version: [TYPE / VERSION]
- Clauses to review: [PASTE ONLY APPROVED TEXT OR REFERENCE AN APPROVED PROJECT FILE]
- Organization-approved playbook: [APPROVED POSITIONS, FALLBACKS, AND ESCALATION RULES]
- Commercial context: [DEAL VALUE, TERM, PRODUCT/SERVICE, BUSINESS OWNER]
- Governing-law or jurisdiction information supplied by counsel: [IF AVAILABLE]
- Known non-negotiables: [LIST]

TASK
Create an internal issue log. For each relevant clause, return:
1. Section number and exact quoted clause excerpt.
2. Playbook position that applies, or “no approved position supplied.”
3. Observed variance from the playbook.
4. Business impact question for the deal owner.
5. Escalation level: counsel required, commercial decision required, or routine review.
6. A neutral question or drafting option for counsel to consider, clearly labelled as a draft for review.

GUARDRAILS
Do not state that a clause is enforceable, illegal, standard, or acceptable. Do not invent law, precedent, market practice, authority, or a playbook rule. Do not give final legal advice, make a final redline, or recommend sending text to a counterparty. Flag missing jurisdiction, missing playbook rules, and ambiguous clauses.

OUTPUT
Start with a short scope-and-missing-information note. Then produce the issue log in a table. End with an escalation list and a checklist for attorney review.

Use a clear escalation taxonomy

EscalationTypical triggerAppropriate next action
Counsel requiredNo approved position, unusual law/jurisdiction, material liability, IP, privacy, security, employment, regulatory, or dispute issue.Preserve the clause excerpt, context, and question; send it to the designated attorney or specialist.
Commercial decision requiredThe playbook allows options but the acceptable trade-off depends on price, scope, service levels, timing, or risk appetite.Ask the accountable business owner to select an approved fallback before counsel drafts language.
Routine reviewThe clause matches an approved position and no material context is missing.Record the comparison for the reviewer; do not treat the AI output as final approval.

Human review checklist

  1. Confirm the model received the correct document version and only authorized material.
  2. Verify every clause quote and section reference against the source agreement.
  3. Check every playbook comparison against the current, approved playbook.
  4. Ensure missing context and jurisdiction limits are visible rather than guessed.
  5. Route all counsel-required items and record the final human decision outside the model output.

Frequently asked questions

Can this workflow generate a redline to send to a counterparty?

It can organize draft language options for qualified counsel to consider, but it should not be treated as a final legal redline or sent without attorney approval.

Should we upload a whole contract to a public AI tool?

Only use an AI environment that your organization has approved for that document and data type. Follow your confidentiality, privacy, retention, and access-control requirements before uploading anything.

What if the playbook has no answer?

Record the missing rule and escalate it. A model should not fill a policy gap by inventing legal or commercial positions.

Related workflow resources

For a general structure for clear instructions, constraints, and review points, see The Enterprise LLM Prompt Engineering Framework. Use PromptGrade only to inspect prompt structure; it is not a legal-review tool.

Editorial and use standard

Use this workflow to create a reviewable first draft, not to replace the judgment of the person accountable for the result. Verify facts, claims, sources, permissions, brand fit, and the final decision before publishing, sending, or acting on any AI-assisted output.

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