# Ambiguity Stress Test

Adversarially stress-tests a legal text, a contract, statute, regulation, or judicial...

- Repository: https://github.com/lawve-ai/awesome-legal-skills (919 stars)
- Category: Testing
- License: see repository
- Last updated: 2026-10-19
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add lawve-ai/awesome-legal-skills --skill ambiguity-stress-test -g -a claude-code -y`
Codex: `npx skills add lawve-ai/awesome-legal-skills --skill ambiguity-stress-test -g -a codex -y`
Cursor: `npx skills add lawve-ai/awesome-legal-skills --skill ambiguity-stress-test -g -a cursor -y`
Gemini CLI: `npx skills add lawve-ai/awesome-legal-skills --skill ambiguity-stress-test -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add lawve-ai/awesome-legal-skills`

## Description

Adversarially stress-tests a legal text, a contract, statute, regulation, or judicial opinion, for interpretive ambiguity: it finds the seams where the people governed by it will later disagree about what it means and turns each into a concrete dispute scenario with both sides' arguments, the likely outcome, and a fix. Use it whenever someone wants to pressure-test, red-team, audit, or find weak spots, loopholes, gaps, ambiguities, or drafting problems in a legal document; whenever a drafter wants to tighten a contract, statute, regulation, or opinion before it issues; whenever a litigator wants to mine an opinion or contract for arguments; or whenever someone hands over a legal text and asks where it will be fought over or for issue-spotting. Trigger it for contract review, statutory-ambiguity analysis, judicial-opinion scope analysis, and drafting QA, even if the user never says "stress-test" or "ambiguity.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Interpretive-Ambiguity Stress-Test

Adversarially stress-test a legal text for the places where the people governed by it will later disagree about what it means. For each weak seam, produce a concrete dispute scenario: a realistic fact pattern, both sides' arguments, the likely outcome, and a fix. The text can be a contract, a statute, a regulation, or a judicial opinion.

The skill rests on one principle, **generalize the detector, keep the resolver modular.** The machinery that *finds* ambiguity (parse, scan, construct an edge-case scenario, frame two plausible readings) is the same for every legal text. The machinery that *resolves* it is not: contract ambiguity is settled by recovering the parties' bargain, statutory ambiguity by the canons of construction, regulatory ambiguity by the canons plus the enabling act, and a judicial opinion's by the doctrines of precedent. So the skill has a general **core** (this file) and four domain **profiles** (in `resources/`). Run the core; load the one profile that matches the document.

The product is **disputes, not flags.** A linter says "this term is vague." This skill instead invents the two people who would each, plausibly, win if their reading prevailed, and the money or liberty riding on the answer. A latent ambiguity is invisible to a non-specialist until someone shows them the collision it will cause.

## Workflow

- **Step 0**, Select the profile and read its reference file.
- **Step 1**, Parse the text.
- **Step 2**, Scan for defects.
- **Step 3**, Construct a scenario for each confirmed defect.
- **Research**, between Steps 3 and 4, establish what sources are available and check the surviving scenarios against them. Statute, regulation and opinion profiles only; the contract profile skips it.
- **Step 4**, Emit the scenario records.

The rest: https://github.com/lawve-ai/awesome-legal-skills/blob/HEAD/skills/ambiguity-stress-test-seth-chandler/SKILL.md