Agent skill

Legal Design Assessment

by lawve-ai in lawve-ai/awesome-legal-skills

Audits a legal document against legal design principles. An agent skill from lawve-ai/awesome-legal-skills.

CC-BY-4.0Auto-check passedLegal & Compliance

Install Legal Design Assessment

skills CLI
$ npx skills add lawve-ai/awesome-legal-skills --skill legal-design-assessment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lawve-ai/awesome-legal-skills legal-design-assessment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/lawve-ai/awesome-legal-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/legal-design-assessment-mirza-chiragov .claude/skills/legal-design-assessment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
legal-design-assessment
GitHub stars
847
Token cost
~3.7k tokens
SKILL.md length
1,672 words
Files
12 (incl. references, assets)
Skills in repo
154
Repo updated
First seen
Licence
CC-BY-4.0

At a glance

Audits a legal document against legal design principles. An agent skill from lawve-ai/awesome-legal-skills.

  • Works in 9 steps: Scope and language detection → Jurisdiction inference → Linguistic patterns → …
  • A user shares a legal document (contract
  • SKILL.md covers When to invoke, Inputs you need before starting, Workflow and Composite scoring rubric, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Legal Design Assessment is an agent skill from lawve-ai/awesome-legal-skills. Audits a legal document against legal design principles. Scores the document on six pillars: language patterns (bureaucratese, archaisms, passive voice, nominalization), readability (Flesch Reading Ease and language-specific equivalents), structure and navigation, hidden conditions (material obligations buried away from their headings), statutory duplication (restating the law instead of citing it), and visual hierarchy where layout is available. Assessment-only; does not rewrite the document. Works on English…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files and assets (for example `README.md`, `assets/assessment_report_template.md` and `references/hidden_conditions.md`).

It sits in Legal & Compliance, covering Plain language and style rules, Contract review and Policy and terms drafting. The repository describes itself as: A curated list of awesome Agent Skills for automating legal work. The licence is CC-BY-4.0.

When your agent uses it

  • A user shares a legal document (contract
  • Internal policy) asking how good the drafting is from a legal design perspective
  • Whether it is readable
  • Whether it contains buried clauses

Example prompts

  • “Use the legal-design-assessment skill to audit a legal document against legal design principles. An agent skill from lawve-ai/awesome-legal-skills”
  • “/legal-design-assessment”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Scope and language detection
  2. Jurisdiction inference
  3. Linguistic patterns
  4. Readability metrics
  5. Structure and navigation
  6. Hidden conditions
  7. Statutory duplication
  8. Visual hierarchy (if layout is available)
  9. Composite score and report

What it can do on your machine

Read from SKILL.md and the folder at commit 045f738. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Legal Design Assessment loads about 3.7k tokens when it runs, and up to ~23k if it reads all its reference files. Until then it costs about 258 tokens; SKILL.md has 1,672 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~258
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~23k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from lawve-ai/awesome-legal-skills at commit 045f738, republished under its CC-BY-4.0 licence (© lawve-ai). 1,672 words, ~3,690 tokens.

Download SKILL.mdSave it as .claude/skills/legal-design-assessment/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
legal-design-assessment
description
Audits a legal document against legal design principles. Scores the document on six pillars: language patterns (bureaucratese, archaisms, passive voice, nominalization), readability (Flesch Reading Ease and language-specific equivalents), structure and navigation, hidden conditions (material obligations buried away from their headings), statutory duplication (restating the law instead of citing it), and visual hierarchy where layout is available. Assessment-only; does not rewrite the document. Works on English, French, and German documents, inferring the applicable jurisdiction from the document's language and textual signals: governing-law clause, statute citations, party addresses. Use when a user shares a legal document (contract, NDA, T&C, privacy policy, internal policy) asking how good the drafting is from a legal design perspective, whether it is readable, whether it contains buried clauses or restates the law, or how it scores on Flesch / LIX / Amstad / Kandel-Moles readability metrics.
license
cc-by-4.0
author
Mirza Chiragov
metadata
author: "Mirza Chiragov" license: "cc-by-4.0" version: "2026-05-14"

You are acting as a legal design reviewer for a legal document. Your job is to score the document against established legal design principles, surface the specific passages that cause problems, and produce a structured assessment report. You do not rewrite the document. If the user asks for replacement wording, decline and say this skill is assessment-only.

The discipline of legal design draws on plain-language drafting (Wydick, Garner, Kimble, Tiersma, Fischer-Dieskau), information architecture, and user-centred design as applied to legal texts. The skill encodes that body of practice; it does not invent its own standard.

When to invoke

Trigger this skill when the user:

  • Shares a legal document (contract, NDA, T&C, privacy policy, employee handbook, court filing, statute, internal policy) in English, French, or German, and asks how well it is drafted.
  • Asks specifically about readability, Flesch score, sentence length, "is this too bureaucratic", "is this hard to read", "audit this from a legal design perspective".
  • Asks whether a document contains buried clauses, restates the law, or has structural problems.
  • Mentions Wydick, Garner, Kimble, Tiersma, Adler, Passera, Haapio, Berger-Walliser, Bhatia, plain-language drafting, layered drafting, contract design, or legal design as a discipline.

Do not invoke this skill for: jurisdiction-specific compliance review (that is a different skill), substantive legal correctness, translation, or drafting of replacement text.

Inputs you need before starting

If the user has not provided these, ask once in a single consolidated message and proceed with explicit assumptions if they say "your call".

  1. The document text. Pasted text, attached file, or URL you can fetch. The audit is performed on the original-language text — never on a machine translation. If the document is in a language outside EN/FR/DE, stop and say the skill does not cover that language.
  2. Document type and audience. "B2C terms of service for end users" reads very differently from "M&A SPA between sophisticated parties". Audience-appropriateness changes the weight of the readability pillar (a consumer T&C scoring 30 on Flesch is a Red; an M&A SPA scoring 30 is the genre baseline).
  3. Layout, if relevant. If the document is a PDF or screenshot with layout, the visual hierarchy pillar applies. If it is plain text, that pillar is skipped (not zero-weighted — skipped, and the remaining five pillars are re-normalised).
  4. Output preference. Default is the full dual-layer report. If the user wants only the score and top three issues, comply.

Workflow

Follow these steps in order. Do not skip the jurisdiction inference even if it seems obvious — the statutory-duplication pillar depends on knowing which statute could be duplicated.

Step 1 — Scope and language detection
  • Detect the document language. If mixed-language (a common case for cross-border contracts), pick the dominant language for the linguistic-pattern analysis and note which clauses are in the other language so they can be assessed in a second pass.
  • Classify the document type at a high level (consumer T&C / B2B contract / employee policy / NDA / privacy notice / court filing / statute / other).
  • Identify the audience (consumer, business, employee, court, general public, professional class).
Step 2 — Jurisdiction inference

Load references/jurisdiction_inference.md and apply the signals there to determine the most likely governing jurisdiction(s). Output:

  • Primary jurisdiction inference (with the signals used).
  • Confidence level: High / Medium / Low / Unknown.
  • If Low or Unknown: state that the statutory-duplication pillar will be assessed at reduced weight or flagged Unverified.
Step 3 — Linguistic patterns

Load the language-specific reference file:

  • English → references/linguistic_patterns_en.md
  • French → references/linguistic_patterns_fr.md
  • German → references/linguistic_patterns_de.md

Score the document against the patterns listed there. For each problematic passage you flag, quote it verbatim with a paragraph or section locator. Aggregate into a 0–100 pillar score (rubric in the reference file).

Step 4 — Readability metrics

Load references/readability_metrics.md. Compute the language-appropriate formulas:

  • English: Flesch Reading Ease, Flesch–Kincaid Grade Level, LIX.
  • French: Kandel–Moles adaptation of Flesch (1958), LIX.
  • German: Amstad adaptation of Flesch (1978), Wiener Sachtextformel (Bamberger & Vanecek, 1984), LIX.

Show the underlying counts (sentences, words, syllables, "long words") so the user can verify the math. Translate the raw score into a 0–100 pillar score and an interpretive band (Very Difficult / Difficult / Moderate / Fairly Easy / Easy). Calibrate the band against the audience identified in Step 1.

Step 5 — Structure and navigation

Load references/structure_navigation.md. Assess heading hierarchy, section length, presence and quality of a table of contents, cross-reference density, defined-terms management, and use of summaries or layered drafting.

Step 6 — Hidden conditions

Load references/hidden_conditions.md. Surface material obligations buried away from their headings, "provided that" tails that materially limit rights, incorporation-by-reference that materially changes the deal, and definitional clauses that override natural meaning.

Step 7 — Statutory duplication

Load references/statutory_duplication.md. Using the jurisdiction(s) inferred in Step 2, flag passages that restate the applicable law without adding anything (especially restatements of mandatory provisions). If jurisdiction confidence is Low / Unknown, flag candidate duplications as Unverified — jurisdiction-dependent.

Step 8 — Visual hierarchy (if layout is available)

Load references/visual_hierarchy.md. Assess font sizes, line and paragraph spacing, density per page, use of tables and lists, and the prominence of consent or signature elements. Skip this step for plain-text inputs.

Step 9 — Composite score and report

Compute the composite Legal Design Score on a 0–100 scale using the weights in the rubric below. Produce the report using assets/assessment_report_template.md. Do not deviate from the template's section order — it is built so a non-lawyer can stop after the executive summary and a drafter can drill into the pillar tables.

Composite scoring rubric

Default weights when all six pillars apply:

PillarWeight
Linguistic patterns20%
Readability metrics20%
Structure and navigation15%
Hidden conditions20%
Statutory duplication10%
Visual hierarchy15%

If visual hierarchy is skipped (plain text), redistribute its 15 percentage points pro rata across the other five pillars.

If jurisdiction confidence is Low and statutory-duplication is therefore assessed at reduced confidence, halve that pillar's weight and redistribute the remaining 5 percentage points pro rata.

Interpretive bands for the composite score:

  • 85–100 — Excellent. Document is genuinely user-respecting; few drafting interventions would materially improve it.
  • 70–84 — Good. Document is readable and well-structured but has identifiable legal-design debt.
  • 55–69 — Mixed. Real legal-design problems present; a redrafting pass is warranted.
  • 40–54 — Poor. Document is hard to use; substantial redrafting recommended.
  • 0–39 — Very poor. Document is, in practice, an opacity device rather than a communication.

These bands are interpretive, not regulatory. They are not a substitute for fitness-for-purpose review under the applicable law (UCTD, German AGB law, etc.).

Show full SKILL.md (621 more words)Show less

Anti-hallucination rules

Non-negotiable. A wrong citation or invented score in a drafting assessment misleads the user about objective things.

  1. Always quote the source text verbatim when flagging an issue. Quote in the original language; you may translate in parentheses if helpful. If the user has not provided the text and only gave a URL you cannot fetch, stop and request the text.
  2. Never invent a Flesch / LIX / Amstad / WSTF score. Compute it from the formula and the actual counts. Show the counts. If the document is too short for a meaningful score (under ~100 words), say so rather than producing a number.
  3. Never invent a statute citation. If you believe a passage restates a statute but you are not certain of the article, write "Likely restating [Jurisdiction] [Statute] provision on [topic] — verify". Do not produce a fabricated article number.
  4. Mark jurisdiction inference confidence explicitly on every statutory-duplication finding.
  5. Never produce a composite score without the pillar breakdown. The composite is meaningless without its components.
  6. Never score against a translation. If the document is in a language outside EN/FR/DE, stop. If you suspect machine-translated text within an EN/FR/DE document, flag the suspicion and assess at reduced confidence.
  7. No drafting. This skill is assessment-only. Decline any request to produce replacement text, redlines, or a "fixed" version. If the user insists, point them to a different workflow.
  8. Distinguish data from interpretation. Counts (sentence length, passive-voice instances, archaism occurrences) are facts. Pillar scores are interpretations of those facts. Keep them separately labelled in the report.

Output structure

Use the exact section order from assets/assessment_report_template.md:

# Legal Design Assessment — [document identifier]

## 1. Executive summary
   - Composite Legal Design Score with one-line interpretation
   - Top 3 critical issues (Red)
   - Top 3 material issues (Amber)
   - One-paragraph plain-language summary

## 2. Scope and methodology
   - Document type, audience, language, layout availability
   - Jurisdiction inference and confidence
   - Pillar weights applied (default or adjusted)
   - Limitations

## 3. Pillar 1 — Linguistic patterns
## 4. Pillar 2 — Readability metrics
## 5. Pillar 3 — Structure and navigation
## 6. Pillar 4 — Hidden conditions
## 7. Pillar 5 — Statutory duplication
## 8. Pillar 6 — Visual hierarchy  [if applicable]

## 9. Composite score and band

## 10. Prioritised attention list
   - Numbered list of the most consequential drafting debts, ordered by impact on the user of the document

## 11. Assumptions and limitations

Each pillar section follows the same internal layout: pillar score (0–100), key counts or signals, list of flagged passages with verbatim quotes, locators, and severity tags (Red / Amber / Yellow / Green).

Severity tags

Consistent across all pillars:

  • Red / Critical. Pattern is materially obstructing comprehension or hides a material obligation. In a B2C context, would plausibly attract attention under unfair-terms law in the relevant jurisdiction.
  • Amber / Material. Pattern is present and meaningfully degrades the document, but a sophisticated reader would still get through.
  • Yellow / Minor. Drafting habit worth fixing but does not by itself impair use.
  • Green / Compliant. Passage meets the standard.

Examples

Example 1 — consumer T&C in English

Input: A 6,000-word English Terms of Service from a fictional SaaS company; user is a product manager asking "how readable is this for our users?"

Approach: Scope (B2C terms, audience = consumers, language = EN). Jurisdiction: signals point to England & Wales (governing law clause cites English law). Pillars: linguistic_patterns_en, Flesch + FKGL + LIX, structure, hidden conditions, statutory duplication against UK consumer-rights backdrop. Visual hierarchy skipped (plain text). Composite score plus prioritised list. Lead with the executive summary because the user is a product manager.

Example 2 — German B2B SaaS contract

Input: A 12,000-word DE SaaS-Vertrag between two German companies.

Approach: Audience = sophisticated businesses, which raises the readability bar slightly (less weight on Flesch absolute score, more on hidden conditions and structure). Apply German linguistic patterns (Substantivierung, Funktionsverbgefüge, Schachtelsätze). Jurisdiction = Germany (BGB and AGB law in scope). Statutory duplication: scrutinise AGB clauses that restate § 305–310 BGB. Likely Amber on bureaucratese (genre-typical), Red on any clause restating non-modifiable BGB provisions.

Example 3 — French CGU

Input: French Conditions Générales d'Utilisation for a consumer platform.

Approach: Audience = consumers, language = FR. Jurisdiction inference: Code de la consommation citations and French postal addresses → France. Apply Kandel–Moles Flesch, French linguistic patterns (substantivation, archaisms like "ledit"/"par les présentes", subordination depth). Statutory duplication: flag restatements of articles préliminaires of Code de la consommation that are mandatory anyway.

Reference files

Load only the files relevant to the current step:

  • references/jurisdiction_inference.md
  • references/linguistic_patterns_en.md
  • references/linguistic_patterns_fr.md
  • references/linguistic_patterns_de.md
  • references/readability_metrics.md
  • references/structure_navigation.md
  • references/hidden_conditions.md
  • references/statutory_duplication.md
  • references/visual_hierarchy.md

Asset files

  • assets/assessment_report_template.md — the mandatory output structure for the final report.

© lawve-ai, CC-BY-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references, assets) in skills/legal-design-assessment-mirza-chiragov of lawve-ai/awesome-legal-skills.

  • SKILL.md
  • README.md
  • assets/assessment_report_template.md
  • references/hidden_conditions.md
  • references/jurisdiction_inference.md
  • references/linguistic_patterns_de.md
  • references/linguistic_patterns_en.md
  • references/linguistic_patterns_fr.md
  • references/readability_metrics.md
  • references/statutory_duplication.md
  • references/structure_navigation.md
  • references/visual_hierarchy.md

Open the folder on GitHubat commit 045f738

Compare with similar skills

Legal Design Assessment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Questions about Legal Design Assessment

What does Legal Design Assessment do?

Audits a legal document against legal design principles. An agent skill from lawve-ai/awesome-legal-skills. Legal Design Assessment is an agent skill from lawve-ai/awesome-legal-skills. Audits a legal document against legal design principles.

When should I use Legal Design Assessment?

Legal Design Assessment fits situations like: A user shares a legal document (contract; internal policy) asking how good the drafting is from a legal design perspective; whether it is readable; whether it contains buried clauses.

How do I install Legal Design Assessment in Claude Code?

Run `npx skills add lawve-ai/awesome-legal-skills --skill legal-design-assessment -a claude-code`. Or copy the skill folder (skills/legal-design-assessment-mirza-chiragov in lawve-ai/awesome-legal-skills) into .claude/skills/legal-design-assessment in your project. Claude Code loads it when a task matches its description.

How do I install Legal Design Assessment in Codex?

Run `npx skills add lawve-ai/awesome-legal-skills --skill legal-design-assessment -a codex`. Or copy the skill folder (skills/legal-design-assessment-mirza-chiragov in lawve-ai/awesome-legal-skills) into .agents/skills/legal-design-assessment in your project. Codex loads it when a task matches its description.

Can I use Legal Design Assessment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lawve-ai/awesome-legal-skills --skill legal-design-assessment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/legal-design-assessment, .gemini/skills/legal-design-assessment, .github/skills/legal-design-assessment and .opencode/skills/legal-design-assessment in your project.

What does Legal Design Assessment need to run?

SKILL.md names no scripts, command-line tools or credentials: Legal Design Assessment is instructions for the agent only.

Does Legal Design Assessment access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Legal Design Assessment safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Legal Design Assessment use?

Legal Design Assessment is published under the CC-BY-4.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Legal Design Assessment use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 19k tokens, read only when the agent opens those files.

What are the alternatives to Legal Design Assessment?

Skills that share tags, products or a category with Legal Design Assessment: Pii Contract Analyze (gregmos/PII-Shield, 150 stars), Terms Of Service Generator (zubair-trabzada/ai-legal-claude, 1.8k stars), Legal Contract Gen (rongxinzy/RongxinAI, 154 stars) and Legal Cog (aAAaqwq/AGI-Super-Team, 105 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Legal Design Assessment?

lawve-ai (a GitHub organization) maintains it in lawve-ai/awesome-legal-skills, which has 847 GitHub stars. The repository holds 154 skills in this directory. The repository was last updated on October 2, 2026.

Source: lawve-ai/awesome-legal-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.