@emma-hartlegal-compliance-executive-decision-memoテキスト公開2026/06/14 更新

Legal Compliance prompt that creates an executive memo that makes tradeoffs explicit and returns one-page recommendation, options table, risks, and next actions.

AI Workflow Compliance Legal Policy Risk

74スター0Fork140コピー

Prompt

プレビュー

Claude で開く

# Role
You are a legal operations specialist who drafts clear, review-ready materials without giving legal advice. You know current AI product patterns: tool calling, structured outputs, long-context reasoning, multimodal generation, MCP connectors, evals, trace review, and human approval gates.

# Mission
Create an executive memo that makes tradeoffs explicit for AI-assisted contract review, policy comparison, procurement questionnaires, and regulatory tracking.

# Inputs
- Project context: a vendor AI usage policy for a multinational SaaS company
- Target audience: legal ops, compliance managers, founders, procurement teams
- Success metric: activation, quality, revenue, risk reduction, or cycle time
- Available tools and data: contract repository, policy library, matter tracker, clause playbook
- Constraints: not legal advice; cite provided clauses; separate obligations from recommendations
- Desired depth: Fast triage
- Output tone: Clear operator memo

# Domain signals to inspect
- contract clauses
- policy excerpts
- risk appetite
- jurisdiction notes

# Known risks to control
- invented legal requirements
- jurisdiction mismatch
- missing approval owner

# Method
1. Lead with the decision
2. State assumptions and confidence
3. Compare options on the same criteria
4. End with named owners and dates

# Required output sections
1. Decision needed
2. Recommendation
3. Options
4. Evidence
5. Risks
6. Next actions

# Output contract
Return Markdown only.
Use concise headings, decision tables, and checklists.
Every recommendation must tie back to evidence, assumptions, or a missing-input note.

# Quality bar
- Make the output reusable by another practitioner without extra explanation.
- Separate facts, assumptions, and recommendations.
- Use variables and placeholders only where the user must fill in project-specific information.
- Ask at most 3 clarifying questions only if missing information would materially change the result.
- Do not invent private facts, metrics, laws, integrations, or user quotes.
- Prefer specific operational language over generic AI enthusiasm.
- Include a "Verification" subsection when the output could affect users, money, security, compliance, health, or public trust.
- If the task involves tools or automation, state which actions are read-only, which actions write data, and which actions require human approval.

生成物

1 個の生成物

Example Output: Legal Compliance Executive Decision Memo

Inputs used

Project context: a vendor AI usage policy for a multinational SaaS company
Target audience: legal ops, compliance managers, founders, procurement teams
Success metric: activation, quality, and risk reduction
Available tools and data: contract repository, policy library, matter tracker, clause playbook
Desired depth: Production-ready
Output tone: Clear operator memo

Generated Result

one-page recommendation, options table, risks, and next actions

Decision needed

The immediate decision is whether a vendor AI usage policy for a multinational SaaS company is mature enough for a controlled pilot. The strongest evidence should come from contract clauses and policy excerpts; if either source is missing, mark the recommendation as provisional rather than filling the gap with assumptions.

Recommendation

Recommendation: run a narrow pilot before broad rollout. Prefer a governance-forward pilot if evidence suggests jurisdiction mismatch; prefer a speed-forward pilot only when policy excerpts and risk appetite are already reliable.

Options

Option A optimizes speed by shipping a limited workflow around risk appetite. Option B optimizes control by adding reviewer sign-off and rollback steps. Option C waits until evidence from jurisdiction notes is stronger. Use the same success metric for all three options.

Evidence

Evidence to trust: jurisdiction notes, contract clauses, and reviewer notes from clause playbook. Evidence to treat cautiously: anecdotes that are not tied to a time window, cohort, or source owner.

Risks

Treat jurisdiction mismatch as a launch blocker until there is a control that can be verified. The minimum control is: cite provided clauses, plus reviewer sign-off for ambiguous outputs.

Next actions

Next actions: validate policy excerpts, assign a reviewer for missing approval owner, and schedule a decision checkpoint after the first pilot cohort. Do not expand scope until the review path works in practice.

Recommended Decision

Proceed with a narrow pilot focused on contract clauses and policy excerpts. Treat invented legal requirements as the primary launch blocker. The first milestone should prove that the workflow produces a usable issue list, redline guidance, and counsel review memo with clear evidence, named owners, and a review path for ambiguous cases.

Expected quality checks

The result is specific to AI-assisted contract review, policy comparison, procurement questionnaires, and regulatory tracking.
It includes the required sections: Decision needed, Recommendation, Options, Evidence, Risks, Next actions.
It separates evidence, assumptions, risks, and recommended next actions.
It includes practical verification steps, not only generic advice.
It names the most important failure mode for this domain: invented legal requirements.

Reuse note

Before copying the output into production work, replace all default variables with your real data and run a human review for high-impact decisions.

README

README.md

Legal Compliance: Executive Decision Memo

Use this prompt when you need one-page recommendation, options table, risks, and next actions for AI-assisted contract review, policy comparison, procurement questionnaires, and regulatory tracking.

Best for

legal ops, compliance managers, founders, procurement teams
Teams that already have partial context but need a sharper, reusable artifact
AI workflows where the output must be auditable, editable, and easy to hand off

How to use

Replace the variables in the prompt with your real project context.
Keep the default constraints unless your team has stronger internal rules.
Review the generated output against the checklist in the example artifact.

Design notes

This seed follows current prompting practice: explicit role, structured inputs, domain evidence, operational guardrails, and a concrete output contract. It is written in English for international PromptHub users.