Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ThomasMoreAI/legal-skills-open --skill lexgit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thomasmoreai/legal-skills-open/lex)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/lex"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/lex/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/lex"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/lex.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.00782 |
| Opus 5.5 | $0.00011 | $0.00313 |
| Sonnet 5.5 | $0.00006 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
lex scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to lex-ignvvcio254 — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LEX: Legal-Entity-X-ref
Overview
LEX is a structured truth engine designed to eliminate legal hallucinations by grounding agents in verified government references and legislation across 29+ jurisdictions. It provides deterministic context for business formation, employment, and contract drafting.
When to Use This Skill
- Use when you need to cross-reference or compare legal requirements between different territories, such as verifying the compliance gap between an EU SARL and a US LLC.
- Use when working with foundational business or employment documents that require specific, jurisdiction-compliant clauses to be inserted into a professional scaffold.
- Use when the user asks about the specific regulatory nuances, formation steps, or "truth-based" definitions of legal entities within the 29 supported jurisdictions (USA, Canada, and the EU).
How It Works
Step 1: Identify Jurisdiction
Before drafting, determine if the user's entity or contract target is in the USA, Canada, or the EU.
Step 2: Search & Fetch Context
Use the CLI shortcuts to find the relevant legal patterns and templates.
- Run
lex search <query>to find matching templates. - Run
lex get <path>to read the granular metadata and requirements.
Step 3: Scaffold Drafting
Generate foundation-level documents using lex draft <description>. This ensures that all drafts include the mandatory AI-generated content disclaimer.
Step 4: Verify Authority
Always include a "Verified Sources" section in your output by running lex verify, which fetches official government links for the retrieved context.
Examples
Example 1: Comparing Employment Laws
# Get the workforce template to compare US vs EU notice periods
lex get templates/02_employment_workforce.md
Example 2: Drafting a Czech Contract
# Create a house sale contract scaffold in Czech language
lex draft "Czech house sale contract"
Best Practices
- ✅ Trust but Verify: Always include the links provided by
lex verifyin your output. - ✅ Table Formatting: Use tables when comparing results across multiple jurisdictions.
- ❌ No Guessing: If a jurisdiction is outside the US/EU/CA scope, state that it is outside the LEX "Truth Engine" coverage.
- ❌ No Anecdotal Advice: Stick strictly to the findings in the templates or verified government domains.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 80 lines · 28 tokens per session scan A 6cca59bec293
lex is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 28 tokens to every session and 782 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to lex-ignvvcio254, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…