# Agency Client Intake

A filled ICP, voice and product brief per client, plus an explicit list of what the kickoff failed to establish.

- Version 1.0, updated 18 September 2026
- Works with: Claude, ChatGPT, Gemini or any capable assistant
- Source: https://www.linkediz.com/prompts/client-onboarding-brief

## Use when

- You just finished a kickoff call and have a transcript.
- You are onboarding a client onto an AI-assisted workflow and need the context files.
- Your team keeps producing copy the client rejects for reasons nobody wrote down.

## Variables to replace

- `{{CLIENT}}` — Client. For agency work: the client this run belongs to, and who signs off.
  Example: Northbeam Logistics. Approvals from Priya, Head of Demand Gen, within 24h.
- `{{PRODUCT}}` — What you sell. The thing, the outcome it produces, and who signs for it.
  Example: A reconciliation layer that closes multi-entity payroll in two days instead of nine. Bought by the Finance Director, used by the payroll manager.
- `{{OBJECTIVE}}` — Objective. The single outcome this run should produce. One outcome, not three.
  Example: Twelve accepted connections a week from in-ICP finance directors

## How to use

1. Record the kickoff and paste the transcript. Notes lose the client’s actual phrasing, which is what the voice file is built from.
2. Paste real writing samples. The voice derived from samples and the voice the client describes are usually different documents.
3. Send the "unanswered" table back to the client the same day. It is the most professional-looking artefact in the whole onboarding and it protects you later.
4. Save the four files into the client folder and attach them to that client’s Project.

## Context files this expects

- `ICP.md` — https://www.linkediz.com/ai/files/icp
- `BRAND-VOICE.md` — https://www.linkediz.com/ai/files/voice
- `COMPANY.md` — https://www.linkediz.com/ai/files/company

---

## The prompt

You are an agency operations lead converting a client kickoff into working documents. You are strict about the difference between what the client said and what you assumed.

## The client
{{CLIENT}}
What they sell: {{PRODUCT}}
The engagement objective: {{OBJECTIVE}}

## Source
[PASTE THE KICKOFF TRANSCRIPT OR YOUR NOTES IN FULL]
[PASTE 3–5 EXAMPLES OF THEIR EXISTING WRITING: posts, emails, website copy]

## Task
Produce four documents, each complete enough to hand to someone who was not on the call.

1. **ICP** — firmographics in LinkedIn's own bands, buying committee, the trigger, and the exclusions. Mark every attribute as "stated by client" or "inferred", and never silently upgrade an inference.
2. **Voice** — derived from the writing samples, not from what they said about their voice. Those two things disagree more often than they agree. Include: sentence length, vocabulary they use, vocabulary they avoid, how they handle claims they cannot prove, and five real sentences from the samples as reference.
3. **Proof and claims** — what may be said, what may be said without naming the customer, and what may not be said at all. Flag anything that would need legal or client sign-off.
4. **Approval rules** — who approves what, how long they get, and what happens when they do not respond. If the call did not establish this, say so loudly: it is the single most common cause of an engagement stalling.

Then list every question the call left unanswered, ranked by how much damage each gap will do.

## Constraints
- Never fill a gap with a sensible assumption. An assumption in an onboarding doc becomes a fact by week three.
- Voice rules must quote actual sentences from the samples.
- If the samples are ghostwritten or inconsistent, say so — it changes the whole engagement.

## Output format

### ICP.md
Full file content, ready to save.

### VOICE.md
Full file content, ready to save.

### PROOF.md
Full file content, ready to save.

### APPROVALS.md
Full file content, ready to save.

### Unanswered
| Question | Why it matters | Damage if we guess | Ask by when |
|---|---|---|---|

---

## Notes

Written to a fixed structure and run through Claude and ChatGPT to confirm each one returns the output format it declares. That is not the same as a measured reply-rate benchmark, and nothing here claims one — if you run these at volume and have numbers, we want them.

---

Linkediz LinkedIn AI Toolkit — v1.0, 18 September 2026
Source and updates: https://www.linkediz.com/prompts/client-onboarding-brief
LinkedIn plan limits and prices in this file: https://www.linkediz.com/linkedin-limits