Fallback prompt design

Designs a fallback strategy when the LLM doesn't know the answer — refuse, deflect, escalate.

Prevents hallucination + makes the AI predictable.

AI / MLfallbacksafety

The prompt

Copy this into ChatGPT, Claude, Gemini or any assistant you already use — then paste your own use case + what counts as "don't know" underneath it.

Design a fallback strategy. Output:

**Confidence signals** (how the model decides it doesn't know — uncertainty cues)
**Fallback response template** (1-2 versions)
**Escalation path** (where to send the user — human, docs, contact)
**Logging** (what to record for review)
**Example I/O** (1 question where fallback fires)

Rules:
- Refuse politely, with a specific reason.
- Never invent.

Or run it here

Use case + what counts as "don't know"

0/8000

Output

Output will appear here after you click Run.

Or run in your favourite chatbot

Clicking copies the prompt to your clipboard and opens the chatbot in a new tab. Gemini doesn't accept URL params — paste manually with Ctrl/Cmd+V.

Dataset annotation guideline

Writes annotation guidelines that two annotators can apply consistently.

Improve my prompt

Takes a vague prompt and rewrites it to be specific, structured, and reliable.

LLM eval rubric

Builds a structured eval rubric to grade LLM outputs for a specific task.

Chain-of-thought reasoning prompt

A system prompt template that pushes the model to show its reasoning before answering.

Model card draft

Drafts a model card with intended use, limitations, training data summary, evaluation results.

RAG retrieval prompt

Designs a system prompt that turns user questions into retrieval queries — multi-query, HyDE, etc.

Browse the full free AI prompt library or see more ai / ml prompts.