Turn vague AI requests into clear, controlled, and verifiable prompts for ChatGPT, Claude, Gemini, and other AI platforms.
ISATVON works in plain text, so you can use the same structured prompt across different AI tools without rebuilding your workflow for every platform. Your prompts remain portable, reusable and easier to maintain even when your preferred AI platform changes.
Most prompts explain what the user wants but fail to define how the AI should complete the task. They often leave critical details unclear, including:
ISATVON converts a basic request into a structured execution brief. This reduces ambiguity, makes assumptions visible and gives the AI a clear response contract.
Weak AI output is often blamed entirely on the model. In practice, many failures begin with incomplete instructions. When sources, constraints, verification steps and expected outcomes are missing, the AI is forced to interpret the task and fill in the gaps. This can lead to:
ISATVON gives each critical part of the task a defined place in the prompt.
A long prompt is not automatically a good prompt. Reliable prompting depends on clearly defining the task, evidence, process, tools, limitations and final deliverable. ISATVON provides a repeatable structure for controlling each of these elements.
Define the AI’s role, exact task and non-negotiable rules before execution begins.
Specify the documents, data or references the AI may use and what it must not invent or assume.
Define the workflow, checks and self-verification steps required before the final response.
State which tools, integrations and capabilities are allowed, required or prohibited.
Set clear requirements for length, audience, tone, language, format, depth and fallback behaviour.
Describe the exact deliverable instead of allowing the AI to choose its own response structure.
Require the AI to disclose uncertainty, missing information, assumptions and confidence levels.
ISATVON transforms a raw request into a structured prompt that can be used across leading generative AI platforms.
Write your task in normal language. It can be short, rough or incomplete.
Organise the request into seven sections covering instructions, sources, execution methods, tools, variables, outcomes and reporting requirements.
Paste the structured prompt into ChatGPT, Claude, Gemini, Perplexity, Copilot, Grok or another capable AI platform.
The AI response should explain what it understood, which sources it used, how it verified the work and what assumptions it made.
ISATVON stands for Instructions, Source, Automation, Tech Stack, Variables, Outcome and Notification. Each section works in two directions: it tells the AI how to perform the task, and it tells the AI what it must report in the response.
Most prompting frameworks focus on organising the user’s request but provide limited control over what the AI reports back. ISATVON creates a two-way structure. The prompt defines how the task should be executed. The response then explains how the task was understood, completed and verified.
This makes AI output easier to inspect, compare, review and reuse in professional workflows.
The model restates the assignment, making incorrect interpretation easier to identify.
Explicit source boundaries reduce the likelihood of invented facts and untraceable statements.
Clear constraints and deliverables reduce the need for repeated correction prompts.
Teams can apply the same prompting structure across departments, projects and AI platforms.
Verification steps, source reporting and assumption disclosure make responses easier to audit.
ISATVON works as portable plain text instead of tying your workflow to one AI product.
ISATVON is designed for tasks where clarity, repeatability, verification and output control matter.
Define approved sources, research boundaries, comparison criteria and citation requirements.
Control the target audience, tone, keywords, structure, factual grounding and call to action.
Specify the development environment, permitted libraries, coding standards, testing requirements and expected output.
Turn unclear business requests into repeatable AI-assisted workflows.
Define datasets, calculation rules, validation checks and reporting formats.
Use ISATVON as a human-readable specification before converting the workflow into stricter machine-executable instructions.
“Review this code and tell me what is wrong.”
This prompt does not define:
Act as a senior Python reviewer. Review only the supplied code for correctness, security and maintainability. Do not assume missing dependencies. Classify findings as Critical, High, Medium or Low. Explain each issue, identify the affected function and provide a minimal corrected snippet. Verify that every recommendation relates directly to the submitted code. Report assumptions separately.
The structured prompt produces a narrower, more relevant and easier-to-review response.
COSTAR helps structure context, objectives, style, tone, audience and response requirements. ISATVON covers similar foundations while adding explicit controls for sources, execution methods, tool use, verification, measurable constraints and assumption reporting.
| Section | What ISATVON adds |
|---|---|
| S Source | Explicit source boundaries |
| A Automation | Execution and verification methods |
| T Tech Stack | Tool-use policies |
| V Variables | Measurable constraints and fallback rules |
| O Outcome | A defined response contract |
| N Notification | Assumption and confidence reporting |
ISATVON is not intended to replace every prompting method. It is better suited to tasks where accuracy, consistency, traceability and output control matter more than speed alone.
Paste a basic request into the ISATVON Prompt Converter. The converter organises your request into instructions, approved sources, execution steps, tool requirements, measurable variables, expected outcomes, and assumption and confidence reporting. Review the generated structure, adjust the details and use it with your preferred AI platform.
“Create a competitor analysis for our SaaS product using the attached research.”
The converter improves prompt structure. It cannot compensate for missing context, unreliable source material or unrealistic requirements.
Start with a structured template instead of building every professional prompt from scratch. The ISATVON Prompt Library includes adaptable templates for:
One framework covering both prompt construction and response reporting.
Use ISATVON as markdown or plain text without installing another platform.
Use the same structure with ChatGPT, Claude, Gemini, Perplexity, Copilot and Grok.
Inspect the framework, adapt it to your workflow and contribute through GitHub.
ISATVON is not the right tool for every AI request.
Stop Re-Prompting. Start Specifying.
Give AI the instructions, evidence, boundaries and output contract it needs to perform useful work. Turn your next vague request into a structured, reviewable and reusable AI prompt.
Open framework. Works with your existing AI tools.
ISATVON is a seven-section framework for creating structured AI prompts. It defines instructions, sources, execution methods, tools, variables, outcomes and notification requirements such as assumptions and confidence.
ISATVON stands for Instructions, Source, Automation, Tech Stack, Variables, Outcome and Notification.
ISATVON uses plain text, so it can be used with ChatGPT, Claude, Gemini, Perplexity, Copilot, Grok and other AI systems that accept natural-language prompts.
COSTAR mainly structures the request. ISATVON also defines execution methods, tool-use policies, verification requirements, measurable constraints and structured reporting of assumptions and confidence.
No framework can guarantee that. ISATVON reduces the risk by establishing source boundaries, requiring verification and making unsupported assumptions more visible.
Yes. ISATVON is an open framework released under the Apache 2.0 licence. It is free to use, adapt and share.
No installation is required to use the basic framework. The template can be copied as plain text or markdown and used with an existing AI platform.
