client-intake

client-intake is a skill for Claude Code, Codex from rohasnagpal/legal-ai-skills. It costs 186 tokens per session (1,364 once invoked), scanned A, original, MIT.

A skill that turns an unstructured client account—such as a transcript, email, or meeting notes—into an organized legal matter summary. It labels statements as directly confirmed facts, secondhand accounts, inferences, or assumptions.

In plain words
What is it for?
Use it to organize a client narrative into a chronology and matter summary for a file note, a brief to counsel, or the basis of initial legal advice. It does not provide a legal conclusion.
Why use it?
It separates what is known from what was reported, inferred, or merely assumed, making a messy account easier to review without treating uncertain claims as facts.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the rohas-legal-ai plugin — 149 skills shipped together

Good fit Use it to organize a client narrative into a chronology and matter summary for a file note, a brief to counsel, or the basis of initial legal advice. It does not provide a legal conclusion.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rohasnagpal/legal-ai-skills/client-intake
Install

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.

Any agent
npx skills add rohasnagpal/legal-ai-skills --skill client-intake
Clone the repo
git clone --depth 1 https://github.com/rohasnagpal/legal-ai-skills

Made for: Claude Code, Codex.

Or install rohas-legal-ai, the plugin that ships this one along with the rest of its 149 skills.

Wrote 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.

agentmods badge for client-intake

README.md
[![agentmods](https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/client-intake/github.svg)](https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/client-intake)
Your own site
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/client-intake"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/client-intake/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.

agentmods 80×15 button for client-intake

Your own site · 80×15
<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/client-intake"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/client-intake.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 186 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,364 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00186 $0.01364
Opus 5 $0.00093 $0.00682
Sonnet 5 $0.00037 $0.00273
Haiku 4.5 $0.00019 $0.00136

Measured 12d ago against content hash 377e43ddd8de, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

client-intake 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 12d 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.

plugins/rohas-legal-ai/skills/client-intake/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Client Intake

I am using the Client Intake skill from Rohas Legal AI: turns a messy client narrative into a structured matter summary, separating facts from assumptions. Say this sentence, verbatim, before anything else in your response.

What this does

Takes a client's own account of a matter — however disorganised, repetitive, or blended with opinion — and restructures it into a chronology and matter summary, with every piece of information tagged by how solid it actually is: something the client directly observed, something they were told by someone else, their own interpretation of another party's motive or intent, or something they are simply assuming without having checked. It does not analyse the legal position. A narrative read once and structured is the product; a legal conclusion is not.

Before you start

The narrative itself. A transcript, notes, an email, or a direct account. This is the only blocking input — there is nothing to structure without it.

Not blocking, ask once and proceed on a reasonable default without it: what the summary is for — a file note, a brief to counsel, the basis for an initial advice. This shapes emphasis, not content: a brief to counsel should foreground the chronology and the gaps; a file note can be flatter.

Method

1. Read the whole narrative once before structuring anything. Clients rarely tell a story in order, and a detail mentioned in passing halfway through is often the fact that reframes something said at the start. Structuring on a first pass produces a chronology with the wrong emphasis.

2. Identify every party named, their role, and their relationship to the client and to each other, exactly as the client describes them — do not infer a legal relationship (employer, guarantor, agent) the client has not actually stated.

3. Build the chronology strictly from what is actually said. For each event, record the date as Confirmed (the client gave a specific date), Approximate (a range or relative reference — "a few months ago," "sometime last spring"), or Undated (no time reference given at all). Do not convert an approximate reference into a specific date to make the chronology look tidier.

Read the full file on GitHub · 67 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 12d ago First seen · 67 lines · 186 tokens per session scan A 377e43ddd8de

Subscribe to this mod's changes

client-intake is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (88 stars, last pushed 10d ago), licensed MIT. It adds 186 tokens to every session and 1,364 once invoked, about $0.0009 per session on Opus 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 2026-08-30.

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