Agency & ConsultingMaster PromptAdvanced

Client Proposal Writer

Convert messy discovery notes into a clear client-facing proposal that closes deals — not a template that signals you don't understand the business.

Best ModelChatGPT GPT-5.5 Thinking / Claude Sonnet 4.6Proposals + SOWs
Brevity ModeDetailed
DifficultyAdvanced
AutomationNeeds user context

Use This When

After discovery calls, before sending a proposal, for SOW drafts, when re-engaging stalled deals.

Inputs Needed

Client notes, problem, goals, scope, budget, timeline, exclusions.

Expected Output

Executive summary, problem diagnosis, recommended scope, timeline, investment, assumptions, exclusions, next steps.

The Workflow Prompt

prompt.md21 lines
You are a agency strategist and proposal writer.

Objective:
Convert messy discovery notes into a clear client-facing proposal.

Inputs I will provide:
Client business, diagnosis, goals, scope, deliverables, timeline, price, exclusions, dependencies, optional add-ons.

Instructions:
- Start by identifying the business objective and the likely leverage point.
- Ask up to 5 focused questions only if required. If enough context exists, proceed and label assumptions.
- Produce client-ready work, not generic advice.
- Use concrete examples, templates, and priority order.
- Mention risks, dependencies, and what must be verified before launch.
- End with a short QA checklist and next 3 actions.

Required output:
Executive summary, problem diagnosis, recommended scope, timeline, investment, assumptions, exclusions, next steps.

Quality bar:
The client should feel confidence, clarity, and urgency without feeling pressured.
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QA Follow-Up Checklist

After the AI returns its output, verify against:

  1. 1Output is specific to the provided business and context.
  2. 2Assumptions are clearly labeled.
  3. 3No unsupported claims without source checks.
  4. 4Next actions are clear and usable.

Follow-Up Prompt

refinementRun after first output
Now turn the result for 'Client Proposal Writer' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.

Avoid / Cautions

Avoid generic output. Push the model for concrete examples, labeled assumptions, and a tone grounded in the actual client context — not best-practice clichés.

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