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🔗 AI Prompt Workflow Builder

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Visually design multi-step AI prompt chains with conditional branching, variable injection, and template reuse

Zero Dependencies · Works Offline

📝 Workflow Design

📋 Workflow Preview (JSON)

Click "Add Step" to start designing your workflow...

📦 Preset Templates

📄 Content Generation Pipeline
🔍 Code Review Chain
📊 Data Analysis Pipeline
🌐 Multi-Language Translation
📝 Summary Generation Chain

📊 Workflow Stats

Steps0
Conditions0
Variables0
Est. Tokens~0

AI Prompt Workflow Builder - Visual Multi-Step Prompt Chain Designer

The AI Prompt Workflow Builder is a free online tool that helps you visually design and orchestrate multi-step AI prompt chains. As AI application scenarios become increasingly complex, single prompts often cannot complete complex tasks. Multiple prompts need to be combined in a logical sequence to form a workflow, enabling more powerful AI processing capabilities.

Core Features

Use Cases

AI prompt workflows are suitable for complex tasks requiring multi-round AI processing:

What is a Prompt Chain?

A Prompt Chain is a technique that combines multiple AI prompts in a logical sequence. Unlike single prompts, Prompt Chains break down complex tasks into multiple sub-steps, where each step's output serves as the next step's input, forming a chain processing flow. This approach can improve the accuracy and consistency of AI output, especially for scenarios requiring multi-step reasoning or iterative optimization.

How to Design an Efficient AI Workflow?

Key principles for designing efficient AI workflows: 1) Each step should have a single responsibility with clear, testable output; 2) Use variable passing appropriately to avoid information loss; 3) Set conditional branches to handle exceptions; 4) Control the total number of steps to avoid context window overflow; 5) Add output format requirements for each step to ensure downstream parsability.

Frequently Asked Questions

What is an AI Prompt Workflow?▼
An AI Prompt Workflow is a chain structure that arranges multiple AI prompts in a logical sequence, where the output of one step can be used as input for the next. It is ideal for complex tasks requiring multi-round AI processing, such as content generation pipelines, data analysis pipelines, and code review chains.
How to design a prompt workflow?▼
Steps to design a prompt workflow: 1) Break down the task into sub-steps; 2) Write prompt templates for each step; 3) Define variable passing between steps; 4) Set conditional branching logic; 5) Test and optimize each node's output.
What variable syntax is supported?▼
Double curly brace syntax {{variable_name}} is supported for referencing variables. Variable sources include: user input, previous step output, and built-in system variables (e.g., date, timestamp). Conditional branches support {{prev_output}} to reference the previous step's output.
Is workflow data uploaded?▼
No. This tool runs entirely in the browser locally. All workflow design, editing, and export operations are performed on the client side. No data is uploaded to any server.
Which platforms support the exported JSON format?▼
The exported JSON workflow format is a universal standard format that can be adapted to mainstream AI Agent frameworks such as LangChain, AutoGPT, and CrewAI. You can also make simple format conversions based on specific platform requirements.
How to implement conditional branching?▼
Add conditional judgments in step nodes to select different subsequent paths based on the output of the previous step. For example: if the previous output contains 'error', take the fix branch; otherwise, proceed to the next step. Conditions support keyword matching, length checking, regex matching, and more.

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`; } }); updateStats(); } function updateStepField(id,field,val){const s=steps.find(s=>s.id===id);if(s)s[field]=val;updatePreview();updateStats()} function updateStepVariables(id,val){const s=steps.find(s=>s.id===id);if(s)s.variables=val.split(',').map(v=>v.trim()).filter(Boolean);renderSteps();updatePreview()} function updatePreview(){ const wf={name:document.getElementById('workflow-name').value,description:document.getElementById('workflow-desc').value,version:'1.0',steps:steps.map((s,i)=>{if(s.type==='step')return{step:i+1,type:'prompt',name:s.name,template:s.prompt,variables:s.variables||[],inputFrom:i>0?steps[i-1].name:'user'};return{step:i+1,type:'condition',name:s.name,condition:s.condition,trueBranch:s.trueBranch,falseBranch:s.falseBranch}})}; document.getElementById('workflow-preview').textContent=JSON.stringify(wf,null,2); } function updateStats(){ document.getElementById('stat-steps').textContent=steps.filter(s=>s.type==='step').length; document.getElementById('stat-conditions').textContent=steps.filter(s=>s.type==='condition').length; const totalVars=steps.reduce((acc,s)=>acc+(s.variables||[]).length,0); document.getElementById('stat-variables').textContent=totalVars; const totalChars=steps.reduce((acc,s)=>acc+(s.prompt||'').length+(s.trueBranch||'').length+(s.falseBranch||'').length,0); document.getElementById('stat-tokens').textContent='~'+Math.round(totalChars/4); } function exportJSON(){ updatePreview();const text=document.getElementById('workflow-preview').textContent; const blob=new Blob([text],{type:'application/json'});const a=document.createElement('a'); a.href=URL.createObjectURL(blob);a.download=(document.getElementById('workflow-name').value||'workflow')+'.json';a.click(); } function copyJSON(){updatePreview();const text=document.getElementById('workflow-preview').textContent;navigator.clipboard.writeText(text).then(()=>showToast())} function importJSON(){ const input=document.createElement('input');input.type='file';input.accept='.json'; input.onchange=e=>{const f=e.target.files[0];if(!f)return;const r=new FileReader(); r.onload=ev=>{try{const wf=JSON.parse(ev.target.result); document.getElementById('workflow-name').value=wf.name||''; document.getElementById('workflow-desc').value=wf.description||''; steps=[];stepCounter=0; (wf.steps||[]).forEach(s=>{stepCounter++; if(s.type==='condition')steps.push({id:stepCounter,type:'condition',name:s.name,condition:s.condition||'',trueBranch:s.trueBranch||'',falseBranch:s.falseBranch||''}); else steps.push({id:stepCounter,type:'step',name:s.name,prompt:s.template||'',variables:s.variables||[]}); });renderSteps();updatePreview(); }catch(err){showToast('Invalid JSON: '+err.message)}};r.readAsText(f)}; input.click(); } function clearAll(){if(confirm('Clear all steps?')){steps=[];stepCounter=0;renderSteps();updatePreview()}} function loadTemplate(type){ steps=[];stepCounter=0; const templates={ content:[ {type:'step',name:'Topic Analysis',prompt:'Analyze the core points and target audience of the following topic: {{topic}}',variables:['topic']}, {type:'step',name:'Outline Generation',prompt:'Based on the following analysis, generate a structured article outline: {{prev_output}}',variables:[]}, {type:'step',name:'Content Writing',prompt:'Write the complete article based on the following outline: {{prev_output}}',variables:[]}, {type:'condition',name:'Quality Check',condition:'prev_output.length < 500',trueBranch:'Content is too short, please expand the details and arguments: {{prev_output}}',falseBranch:'Please polish the following content to improve fluency: {{prev_output}}'} ], 'code-review':[ {type:'step',name:'Code Analysis',prompt:'Analyze the functionality and structure of the following code: {{code}}',variables:['code']}, {type:'condition',name:'Security Check',condition:'prev_output.includes("security")',trueBranch:'Detail the security risks in the following code and provide fix suggestions: {{prev_output}}',falseBranch:'Security check passed, continue with performance analysis: {{code}}'}, {type:'step',name:'Performance Optimization',prompt:'Analyze performance bottlenecks in the following code and provide optimization suggestions: {{prev_output}}',variables:[]}, {type:'step',name:'Documentation',prompt:'Generate a complete code review document based on the above analysis: {{prev_output}}',variables:[]} ], 'data-pipeline':[ {type:'step',name:'Data Cleaning',prompt:'Clean the following raw data, removing invalid and duplicate entries: {{raw_data}}',variables:['raw_data']}, {type:'step',name:'Format Conversion',prompt:'Convert the following cleaned data to standard JSON format: {{prev_output}}',variables:[]}, {type:'step',name:'Statistical Analysis',prompt:'Perform statistical analysis on the following JSON data, output key metrics: {{prev_output}}',variables:[]}, {type:'step',name:'Report Generation',prompt:'Generate a readable data analysis report based on the following statistics: {{prev_output}}',variables:[]} ], translation:[ {type:'step',name:'Source Analysis',prompt:'Analyze the language features, style, and key terminology of the following text: {{source_text}}',variables:['source_text']}, {type:'step',name:'Translation',prompt:'Translate the source text from the above analysis into {{target_lang}}, maintaining the original style and terminology accuracy: {{prev_output}}',variables:['target_lang']}, {type:'condition',name:'Proofreading',condition:'prev_output.includes("translation")',trueBranch:'The following translation has issues, please correct: {{prev_output}}',falseBranch:'Please polish the following translation for natural fluency: {{prev_output}}'} ], summarize:[ {type:'step',name:'Key Information Extraction',prompt:'Extract all key information and core arguments from the following long text: {{long_text}}',variables:['long_text']}, {type:'step',name:'Summary Generation',prompt:'Based on the following key information, generate a concise summary (max 200 words): {{prev_output}}',variables:[]}, {type:'condition',name:'Length Check',condition:'prev_output.length > 200',trueBranch:'The following summary exceeds 200 words, please condense: {{prev_output}}',falseBranch:'Summary length is appropriate, please optimize the language: {{prev_output}}'} ] }; const tpl=templates[type];if(!tpl)return; tpl.forEach(s=>{stepCounter++;addStep({...s,id:stepCounter})}); const names={content:'Content Generation Pipeline','code-review':'Code Review Chain','data-pipeline':'Data Analysis Pipeline',translation:'Multi-Language Translation',summarize:'Summary Generation Chain'}; document.getElementById('workflow-name').value=names[type]||type; document.getElementById('workflow-desc').value='Preset template - '+type; } function escHtml(s){return String(s||'').replace(/&/g,'&').replace(//g,'>').replace(/"/g,'"')} function showToast(){const t=document.getElementById('copy-toast');t.classList.add('show');setTimeout(()=>t.classList.remove('show'),1500)} function toggleFaq(el){el.classList.toggle('open')} loadTemplate('content');