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Review methodology
Prompt Review & QA Methodology
Our manual QA process for verifying that prompts are safe, functional, and perform consistently across different enterprise contexts.
Manual QA Standards
While automated prompt analysis helps grade basic elements, human review is the final gate before a prompt is published in our library. Our review process checks:
- Expert Persona Alignment: Does the AI persona act as a seasoned practitioner rather than a generic assistant?
- Formatting Compliance: We verify that prompts generate structured, drop-in business assets (like briefs or SOW outlines) without trailing AI conversations.
- Exclusion Guidelines: We test whether the prompts successfully block standard LLM jargon, buzzwords, and unsubstantiated claims.
Safety & Compliance Verification
Every guide and template includes clear warnings against:
| Risk Category | Verification Standard |
|---|---|
| Information Leakage | We check that instructions caution users to anonymize confidential client data before model input. |
| Inaccurate Claims | We ensure prompts require grounding inputs so models do not fabricate metrics, testimonials, or specs. |
| Regulatory Compliance | We verify that prompts do not produce content that violates search engine guidelines, ad network compliance, or privacy laws. |
Limitations & Feedback
Prompt testing is an ongoing, empirical process. If you notice a prompt in our library failing to produce consistent results, please report the model, prompt version, and output failure via our contact page. We update our templates weekly to adapt to model updates.