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 firm-self-assessmentgit 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/firm-self-assessment)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/firm-self-assessment"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/firm-self-assessment/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/firm-self-assessment"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/firm-self-assessment.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 | $0.00117 | $0.07467 |
| Opus 5.5 | $0.00047 | $0.02987 |
| Sonnet 5.5 | $0.00023 | $0.01493 |
| Haiku 4.5 | $0.00012 | $0.00747 |
Grade A, and why
firm-self-assessment 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 24d 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.
How it starts
The opening of the file, as written. The whole thing — 454 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/firm-self-assessment
- Load
~/.claude/plugins/config/claude-for-legal/privacy-legal/CLAUDE.md→ firm's own LGPD position, DPA playbook, outputs. - Run the inverted workflow below.
- Mapear quais dados pessoais o escritório trata (origem, categorias, titulares).
- Identificar base legal: sigilo profissional como legítimo interesse + obrigação legal (Estatuto OAB); consentimento para além do mandato (ex.: newsletter).
- Verificar se RIPD é obrigatória (art. 38 LGPD): tratamento em legítimo interesse, risco às liberdades civis, dados de menores, etc.
- Mapear prazos de retenção: prescricional + dever de guarda — citado como 5 anos após fim do mandato (verificar Provimento CFOAB específico).
- Elaborar plano de resposta a incidente de dados (art. 48 LGPD).
- Apresentar achados + decisão árvore para próximas ações.
Avaliação de Conformidade LGPD do Escritório
Escopo e contexto
This skill is for the firm itself, not a client. It inverts the typical privacy-advice model: instead of a privacy-legal team advising a company-client on handling customer data, this skill helps the law firm audit what data it holds about clients, opposing parties, witnesses, and staff — and map the firm's own compliance obligations.
O escritório é um CONTROLADOR de dados pessoais (Art. 5º, VI LGPD) — dados de cliente (nome, e-mail, telefone, CPF, endereço, informações sensíveis sobre litígios) são coletados e processados pelo escritório no exercício do mandato. [verified: https://www.planalto.gov.br/ccivil_03/_ato2015-2018/2018/lei/l13709.htm]
Este skill NÃO substitui um DPA/encarregado — é um diagnóstico de entrada para alertar o sócio sobre o que precisa ser mapeado, regulado, e asegurado.
Purpose
Most law firms have never looked at their own data footprint. They hold vast amounts of personal data about clients, opposing parties, witnesses, and employees — much of it sensitive, long-lived, and sometimes in paper form in a basement. The LGPD (Lei 13.709/2018) applies to law firms as controllers of personal data. This skill walks the firm through:
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.
- 24d ago First seen · 454 lines · 117 tokens per session scan A c746117f32bf
firm-self-assessment is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 117 tokens to every session and 7,467 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-04.
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…