ThinkWithPrompt by SynotticThinkWithPrompt

Answer a customer's security questionnaire accurately

Drafts honest, consistent answers to a security due-diligence questionnaire from your actual controls, flagging gaps.

Legal & ComplianceFew-ShotStandardLegalWriteAnalyzeFill-in Template

The prompt

Help me answer a security questionnaire from a customer or prospect. Questions: [PASTE the questions, or a batch of them] Our security facts: [PASTE what we have: policies, certifications (e.g. SOC 2 Type II, ISO 27001), hosting provider, encryption, MFA, backups, pen test dates, incident response, subprocessors] Previous approved answers: [PASTE past answers - optional] Who reviews before sending: [e.g. "CISO", "legal"] For each question: 1. Draft a direct answer: start with Yes / No / Partial / Not applicable, then 1-3 sentences of supporting detail. 2. Point to evidence we can attach (policy name, report, screenshot) where relevant. 3. If my facts do not cover it, write [NEED INPUT: what is needed and from whom]. Never guess or claim a control we have not confirmed. 4. If the honest answer is No or Partial, add a factual note on compensating controls or roadmap only if I provided one. Rules: - Keep answers consistent across similar questions; flag any contradictions in my source material. - Do not overstate: "encrypted at rest" only if confirmed, no "military-grade", no "fully compliant" claims. - Avoid disclosing sensitive details (internal IPs, exact tool configs) beyond what the question needs. Return a table: # | Question | Answer | Evidence | Confidence (confirmed / needs review) | Notes. Then a list of gaps to raise internally.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • PASTE the questions, or a batch of them
  • PASTE past answers - optional
  • e.g. "CISO", "legal"
  • NEED INPUT: what is needed and from whom

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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