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AI Prompts Library

A collection of prompts for using Large Language Models (ChatGPT, Claude, Copilot, Gemini) alongside the ADS standard. Each prompt is a self-contained Markdown file you can paste into any LLM.

Take a short project description and produce a structured SAD first draft that follows the standard. The output clearly flags every assumption and gap the author must resolve.

Download first-draft.md

Check a completed SAD for completeness, consistency, clarity, and credibility. Returns a structured report of critical findings, major and minor observations, and suggested compliance score adjustments.

Download validate-sad.md

Apply the ADS 0-5 compliance scoring scale to each of the 14 scored sections, with justification and an overall weakest-link score. Returns structured JSON.

Download score-sad.md

CISO-office-style security review covering threat coverage, control gaps, regulatory alignment, and evidence. Produces a structured review with critical issues and conditions for approval.

Download security-review.md

Architecture Review Board (ARB) / Design Authority style review covering strategic fit, appropriateness of rigour, risk management, cost, lifecycle, and portfolio impact. Matches what a real ARB would consider.

Download governance-review.md

Concrete, section-by-section suggestions for raising the quality of a SAD to the next compliance scoring level. No rewriting — the author stays in control of their voice.

Download improve-sad.md


Each prompt works the same way:

  1. Open the prompt file and copy the System Prompt section.
  2. Paste it into your preferred LLM as the system prompt (or as the first message).
  3. Attach or paste your SAD. Optionally attach the JSON Schema for stricter checking.
  4. Follow the usage instruction at the top of each prompt file.

These prompts have been designed for Claude 3.5 / 4 / Opus, GPT-4 / 4o / 5, Gemini 2.x and later, and Copilot. They should work on any instruction-tuned LLM with a context window of at least 32k tokens — which covers all recent major models.

When pasting a SAD into an LLM, you are sharing that content with the LLM provider subject to their terms. For SADs containing sensitive or regulated information, use an enterprise-contracted LLM with data protection guarantees (e.g. Azure OpenAI with data residency, Claude via Bedrock, ChatGPT Enterprise, Gemini Enterprise). Never paste classified or personal data into a consumer LLM.

If you have an effective prompt for a use case we haven’t covered — contract-lawyer review, FinOps review, accessibility review — please contribute via the GitHub repository.