Skip to content
cccskills
FreePublished on GitHub

legal-mdl-audit-ignacio-adrian-lerer

Audits legal AI outputs and workflows for honest compression: unnecessary complexity, false simplicity, excessive caveats, hidden uncertainty and poor cost per legally acceptable output.

The English summary is being prepared. Showing the original description.

Run score Not tested

See how to install

Files included (2)

  • SKILL.md2.0 KB
  • README.md186 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Legal MDL Audit

What this skill does

This skill reviews whether a legal AI answer, prompt, workflow, benchmark result, contract review, memo, compliance report, or agent chain is as simple as it can safely be.

It is inspired by Minimum Description Length: good legal reasoning should explain more with less structure, but never by hiding material uncertainty.

Audit categories

Classify the material as:

  • APPROVE: lean and still legally safe.
  • APPROVE WITH CONSTRAINTS: complexity is justified, but reliance needs stated limits.
  • REWRITE: the output is too complex, repetitive, expensive, or hard to audit.
  • QUARANTINE: the output is falsely simple and hides material uncertainty.

Checklist

Review:

  1. Rules: how many legal propositions are needed?
  2. Exceptions: how many carve-outs or qualifications are doing real work?
  3. Conditions: what facts, dates, forums, sources or procedural states must hold?
  4. Sources: are citations enough, excessive, or missing?
  5. Uncertainty: what must remain visible?
  6. Workflow cost: how many model/tool/human steps were needed?
  7. Output value: did added complexity improve legal acceptability?

Output format

Return:

  1. Verdict.
  2. Complexity drivers.
  3. Hidden uncertainty or omitted hard cases.
  4. What can be simplified.
  5. What must not be removed.
  6. Safer shorter version, if requested.

Rules

  • Do not reward short answers that erase legal uncertainty.
  • Do not reward long answers that add caveats without improving reliance.
  • Prefer cost per legally acceptable output over cost per token or API call.
  • Preserve source gaps, authority boundaries and human-review gates.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

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.

The English summary is being prepared. Showing the original description.

lawve-ai/awesome-legal-skills895Updated Oct 20, 2026

See all skills by lawve-ai

Report a problem with this skill