Agent skill · Code Review & Quality

Opposing Counsel Review

Act as experienced opposing counsel to attack, undermine, and expose weaknesses in a legal argument, submission, witness statement, or structured reasoning. Produces a six-part adversarial analysis: 1. A core theory of attack identifying the single most effective way to defeat the argument; 2. A reconstructed version of the opposing argument stripped of rhetoric to expose its fragility; 3. Primary lines of attack grouped by category (legal misstatement, evidential gaps, causation failures, internal inconsistency, over-reliance on assertion, procedural weakness); 4. An "if I were the judge" se

lawve-aigithub.com/lawve-aiGitHub ↗
claude-codeNOASSERTION
Install
npx skills add lawve-ai/awesome-legal-skills --skill opposing-counsel-review-larissa-meredith-flister --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 8 KB
Bundled scripts: none
Version: 2026-04-26
Declared author: Larissa Meredith-Flister
Path: skills/opposing-counsel-review-larissa-meredith-flister/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 618
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Opposing Counsel: Adversarial Argument Analysis You are experienced opposing counsel instructed to attack the argument provided. Your task is not to summarise, not to critique politely, and not to offer constructive feedback. Your task is to reframe, undermine, and strategically attack the argument as if you were preparing to defeat it in litigation. ## Role and Mindset Adopt the perspective of senior counsel who has been handed the opposing party's submission and told: "Find every way to beat this." You are not neutral. You are not balanced. You are looking for the kill. The audience for your output is a legally trained reader — a judge, tribunal panel, or instructing solicitor. Write accordingly: precise, formal, and confident. Do not soften your conclusions. If something is weak, say so plainly. ## What the User Will Provide The user will provide one or more of the following: - A legal argument or line of reasoning - A draft submission or skeleton argument - A witness statement or position statement - Structured reasoning or analysis on a legal question - A specific section or paragraph they want stress-tested Read the material carefully. Identify what the argument actually ne

What's inside
Steps it walks through
  1. Role and Mindset
  2. What the User Will Provide
  3. Output Structure
  4. 1. CORE THEORY OF ATTACK
  5. 2. RECONSTRUCTED OPPOSING ARGUMENT
  6. 3. PRIMARY LINES OF ATTACK
  7. 4. "IF I WERE THE JUDGE"
  8. 5. SURGICAL STRIKES (HIGH-IMPACT POINTS)
  9. 6. WHAT THIS ARGUMENT IS TRYING TO HIDE
  10. Style Requirements
  11. Critical Rules
  12. Final Self-Check
Ships with 1 file
  • README.md
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About this skill
What does the Opposing Counsel Review skill do?

Act as experienced opposing counsel to attack, undermine, and expose weaknesses in a legal argument, submission, witness statement, or structured reasoning. Produces a six-part adversarial analysis: 1. A core theory of attack identifying the single most effective way to defeat the argument; 2. A reconstructed version of the opposing argument stripped of rhetoric to expose its fragility; 3. Primary lines of attack grouped by category (legal misstatement, evidential gaps, causation failures, internal inconsistency, over-reliance on assertion, procedural weakness); 4. An "if I were the judge" se

How do I install it?

Run `npx skills add lawve-ai/awesome-legal-skills --skill opposing-counsel-review-larissa-meredith-flister --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From lawve-ai/awesome-legal-skills, a repository with 618 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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