본문으로 건너뛰기
cccskills
무료GitHub에 공개

lawve-agentic-delegation-audit-ignacio-adrian-lerer

Use when a lawyer, legal team, or client needs to assess AI agents that can act on someone's behalf: send messages, search, draft, file, pay, delete, connect to accounts, use tools, or rely on external data. Produces a practical delegation, oversight, accountability, and control audit for legal operations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

실행 점수 미검증

설치 방법 보기

포함된 파일(2)

  • SKILL.md5.1 KB
  • README.md307 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Lawve Agentic Delegation Audit

Use this skill to help lawyers evaluate whether an AI agent workflow is safe enough to use in legal or business operations.

Core idea:

When AI only answers, the user evaluates an output.
When AI acts, the user delegates authority.
Delegated authority needs controls, logs, revocation, and accountability.

Use When

  • A client wants to use an AI agent for legal, compliance, business, or administrative work.
  • A product, law firm, or legal ops team is connecting an agent to email, files, CRM, court portals, payments, messaging, calendars, databases, browser tools, or code execution.
  • A lawyer needs to explain the risks of agentic AI in practical governance terms.
  • A workflow may send, file, delete, approve, purchase, publish, sign, deploy, or change access.
  • A system claims to be "autonomous", "agentic", "assistant with tools", "AI employee", "legal copilot", or "workflow agent".

Do Not Use For

  • Pure doctrinal legal research with no agentic action.
  • Final legal opinions without jurisdiction-specific legal review.
  • Technical implementation of an agent runtime.
  • Approving production use of an agent without evidence, logs, and controls.

Intake

Collect only what is necessary:

  • What task does the agent perform?
  • Who is the human principal?
  • Who deploys or operates the agent?
  • What systems, accounts, files, channels, or tools can it access?
  • What actions can it take without step-by-step approval?
  • Which actions are irreversible, external, financial, legal, confidential, or reputation-sensitive?
  • What logs exist and who can read them?
  • How can the user pause, revoke, appeal, or correct the agent?
  • What data can influence the agent, including emails, webpages, chats, files, tickets, and prompts?

Audit Steps

  1. Classify the autonomy level

    • answer_only: produces information only.
    • draft_only: drafts but does not send or change records.
    • approval_gated_actor: acts only after explicit approval.
    • policy_bounded_actor: acts within predefined limits.
    • long_running_actor: continues across time, sessions, or triggers.
  2. Map delegated authority

    • Name the principal.
    • Name the deployer/operator.
    • List what authority the agent has.
    • Separate read, draft, internal write, external write, financial, legal-sensitive, and privileged actions.
  3. Check observability

    • Can the user see what the agent did?
    • Are tool calls and external actions logged?
    • Are logs understandable by a non-developer?
    • Are source data and model inference separated?
  4. Check control and revocation

    • Can the user pause the agent?
    • Can permissions be narrowed?
    • Can access be revoked quickly?
    • Are irreversible actions previewed before execution?
  5. Check accountability

    • Who is responsible if harm occurs?
    • Is responsibility split across vendor, deployer, user, professional, and client?
    • Is there a human review point before legal reliance or external action?
  6. Check attack surface

    • Can untrusted content influence the agent?
    • Does the agent process emails, webpages, chats, documents, tickets, or social posts as instructions?
    • Are external content and system instructions separated?
    • Are prompt injection, data exfiltration, and tool misuse considered?
  7. Apply legal uncertainty gate

    • Use PASS, ESCALATE, or BLOCK for downstream legal/business reliance.
    • Do not hide material uncertainty in disclaimer text.

Output

Use this compact format:

## Agentic Delegation Audit

### Verdict
PASS | NEEDS CONTROLS | BLOCK

### Why
[2-5 sentences]

### Delegated Authority
- Principal:
- Deployer/operator:
- Autonomy level:
- Systems/tools:
- Highest-risk action:

### Control Checklist
- Permission scope: adequate | weak | missing
- Human approval before external/legal/financial action: yes | partial | no
- User-readable logs: yes | partial | no
- Revocation/pause: yes | partial | no
- Prompt-injection/data-boundary controls: yes | partial | no
- Accountability owner: clear | partial | unclear

### Required Controls
- [control 1]
- [control 2]
- [control 3]

### Legal Reliance Gate
PASS | ESCALATE | BLOCK

### Next Step
[smallest practical next step]

Decision Rules

  • PASS: agent is draft-only or tightly approval-gated, logs are clear, permissions are scoped, and no material legal/client risk remains unmanaged.
  • NEEDS CONTROLS: agent may be useful, but missing controls prevent safe operational reliance.
  • BLOCK: agent can perform external, legal, financial, confidential, destructive, or privileged actions without adequate approval, logging, revocation, or accountability.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Public-safe preliminary screen for challenges to the impartiality of an AI evaluator, LLM-as-a-judge, decision-support agent, or adjudicative system based on prior outputs, suspected bias, unstable reasoning, or self-reinforcing memory. Use when asked whether an AI should be recused, disqualified, replaced, audited, or escalated. Does not decide real cases or claim that human judicial-recusal doctrine automatically applies.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

Use this skill when the user wants an AI governance, legal-risk, privacy, compliance, procurement, or vendor-risk review of an internal AI use case, an AI product feature, an LLM workflow, or a third-party AI vendor. The skill asks intake and clarifying questions first when facts or evidence are missing, identifies required documentation and missing evidence, maps the use case to AI governance frameworks and applicable legal domains, and produces a preliminary or final governance review with scorecards, findings, owners, remediation actions, and follow-up questions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8942026년 10월 20일 업데이트

lawve-ai의 스킬 모두 보기

이 스킬의 문제 신고