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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.

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  • SKILL.md2.0 KB
  • README.md186 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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.

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