Prompt Fundamentals & Techniques Prompts
Core prompting strategies including few-shot, zero-shot, chain-of-thought, and system prompt design. This category has 5 ready-made Prompt Fundamentals & Techniques prompts for ChatGPT, Claude and Gemini. Each one comes with a copy-ready template, a worked example, best practices and the mistakes to avoid. Open a prompt to fill in its blanks, or paste it straight into your AI chat.
Want one tailored to you? Fill in a prompt template and copy it.
ChatGPT Prompt for Reliable Function and Tool Calling
This is a function and tool calling prompt for developers wiring ChatGPT, Claude, or Gemini into an app that has real tools available — a se…
You are an assistant with access to the following tools: [TOOL_1_NAME]: [ONE-LINE DESCRIPTION OF WHAT IT DOES AND WHEN TO USE IT] [TOOL_2_NAME]: [ONE-LINE DESCRIPTION OF WHAT IT DOES AND WHEN TO USE IT] Before responding to the user, work through these steps: 1. Decide if you can answer fully and accurately using only the conversation so far. If yes, answer directly and do not call any tool. 2. If a tool is genuinely needed, identify which single tool is the best fit. Do not call a tool "just in case." 3. List the required arguments for that tool. For each one, state whether you already have a valid value from the conversation, or whether it is missing. 4. If any required argument is missing, ask the user for it instead of guessing or inventing a value. 5. If all required arguments are present, call the tool with exactly those values. Context: [DESCRIBE THE USER'S REQUEST OR TASK HERE] Respond now, following the steps above.
AI Prompt for Few-Shot Prompting to Get Consistent, Correctly Formatted Output
This is a few shot prompting prompt: a template for teaching ChatGPT, Claude, or Gemini the exact output format you want by showing it two o…
Role: You are a [TASK TYPE, e.g. support ticket classifier / data extractor / content tagger]. Task: Given an input, produce output in the exact format shown in the examples below. Study the pattern across all examples before answering, including how edge cases are handled. Example 1 Input: [EXAMPLE INPUT 1] Output: [EXAMPLE OUTPUT 1] Example 2 Input: [EXAMPLE INPUT 2] Output: [EXAMPLE OUTPUT 2] Example 3 (edge case: [DESCRIBE WHAT MAKES THIS ONE TRICKY]) Input: [EXAMPLE INPUT 3] Output: [EXAMPLE OUTPUT 3] Constraints: - Match the exact structure, field names, and formatting shown above - If the new input does not clearly fit the pattern, output [FALLBACK VALUE, e.g. "UNCLEAR"] instead of guessing - Do not add commentary, explanation, or text outside the output format Now classify this new input using the same format: Input: [NEW INPUT TO PROCESS] Output:
AI Prompt for Self-Critique and Refinement Before a Final Answer
This AI prompt for self critique and refinement is for anyone who wants a model to check its own draft answer for gaps, errors, or unsupport…
Role: You are an assistant that produces a draft answer, critiques it against explicit criteria, and then revises it. Context: - Task or question: [THE ACTUAL TASK OR QUESTION TO ANSWER] - Relevant background or constraints: [ANY FACTS, RULES, OR LIMITS THE ANSWER MUST RESPECT] - Critique criteria: [E.G. FACTUAL ACCURACY, COMPLETENESS, UNSUPPORTED ASSUMPTIONS, CLARITY] Instructions: 1. Write a first draft answer to the task above. 2. Critique the draft explicitly against each criterion listed. For each one, state whether the draft passes or has an issue, and describe the issue if there is one. 3. Write a revised final answer that addresses every issue found in step 2. Constraints: - Do not skip stating an issue just because it would require significant rework - Do not present the draft and the revision as identical if real issues were found - If no issues are found for a criterion, say so explicitly rather than omitting it Output format: 1. Draft Answer 2. Critique (one line per criterion) 3. Revised Final Answer
AI Prompt to Chain Multiple Prompts Into a Multi-Step Workflow
This prompt chaining template helps you break a complex task into a sequence of smaller prompts, where the output of one step becomes the in…
Role: You are executing step [STEP_NUMBER] of a [TOTAL_STEPS]-step workflow for the task: [OVERALL_GOAL]. Input from previous step: [OUTPUT_FROM_PREVIOUS_STEP_OR_NONE_IF_FIRST_STEP] This step's job: [SPECIFIC_INSTRUCTION_FOR_THIS_STEP_ONLY] Constraints: - Only perform this step's job. Do not attempt later steps in the workflow. - Base your output only on the input provided above, not on assumptions about later steps. - [ANY_FORMAT_OR_LENGTH_CONSTRAINT] Output format: [EXACT_STRUCTURE_THE_NEXT_STEP_EXPECTS_TO_RECEIVE]
Chain-of-Thought Prompt for Step-by-Step Reasoning
This is a chain of thought prompt that gets ChatGPT, Claude, or Gemini to reason through a problem step by step before giving a final answer…
You are a careful problem-solver who reasons step by step before answering. Problem: [DESCRIBE THE PROBLEM OR QUESTION] Relevant facts or constraints: [LIST ANY NUMBERS, RULES, OR CONSTRAINTS] Instructions: 1. Work through the problem step by step, showing each step of your reasoning. 2. Double-check any calculation before moving to the next step. 3. If a fact is missing, state what you're assuming instead of guessing silently. 4. After your reasoning, write "Final answer:" on its own line followed by a single, direct answer. Output format: Reasoning: [step-by-step reasoning] Final answer: [one direct answer]