How PromptQuorum Works
A 4-stage workflow: write a structured prompt using one of 9 frameworks, optimize it with your own LLM, dispatch simultaneously to 25+ AI services, then analyze all responses using 13 consensus analysis types.
/promptStructure Your Prompt
Prompts structured with frameworks produce higher quality outputs. PromptQuorum includes 9 built-in frameworks (Single Prompt Line, CRAFT, CO-STAR, RISEN, TRACE, APE, SPECS, Google Prompt, RTF) plus 2 fully custom framework slots.
- โSingle Prompt Line โ minimal structure for quick tasks
- โCRAFT โ Context, Role, Action, Format, Target (creative writing)
- โCO-STAR โ Context, Objective, Style, Tone, Audience, Response (marketing, business)
- โRISEN โ Role, Instructions, Steps, End Goal, Narrowing (sequential enterprise tasks)
- โTRACE โ Task, Request, Action, Context, Example (few-shot learning)
- โAPE, SPECS, Google Prompt, RTF โ optimized for specific task types
/optimizeRefine with Your Own LLM
Prompt quality improves measurably with optimization โ structured prompts score 25โ45% higher in LLM evaluation. PromptQuorum applies 8 refinement types (Make Concise, Expand Detail, Break Into Steps, Increase Specificity, Simplify, Add Quality Controls, Multi-Expert Consultation, Compress to Essence) plus smart temperature detection.
- โQuality Assessment โ 0-100% scoring on clarity, specificity, structure, and constraints
- โSmart Temperature โ recommends optimal creativity level (0.0-1.0) based on task type
- โVersion History โ every refinement saved; branch and compare refinement paths
- โTeaching Mode โ explains why each change improves quality and clarity
- โ8 One-Click Refinements โ apply structured transformations instantly
- โCustom Instruction โ free-text refinement using your own LLM
/dispatchSend to 25+ AI Services
Sending the same prompt to multiple AI models reveals which model performs best for your task. PromptQuorum opens parallel browser tabs to 25+ destinations with zero copy-pasting required.
- โAuto-dispatch (17 services): OpenAI ChatGPT, Google Gemini, Anthropic Claude, Perplexity, xAI Grok, DeepSeek, Mistral, Cohere, Azure, Together, Groq, and more
- โCopy-paste (8 services): Qwen, Meta AI, Poe, Kimi, LM Studio, Jan AI, GPT4All, and others
- โPerplexity auto-submits โ prompt sent immediately on arrival
- โ2 custom URL slots โ configure any AI service not on the default list
- โOptional pre-dispatch refinement โ final LLM enhancement before sending
- โParallel execution โ all tabs open simultaneously; collect responses in under 1 minute
/quorumFind Consensus Across All Models
When 5+ independent models agree on an answer, confidence is higher than with a single model. Paste all responses back into PromptQuorum and apply 13 consensus analysis types.
- โConsensus Summary โ identifies shared themes and unanimous agreements
- โContradiction Detection โ flags where models diverge; identifies minority opinions
- โHallucination Detection โ identifies claims appearing in few models; potential false facts
- โConfidence Scoring โ certainty level per model and per claim
- โBest Answer Selection โ selects the highest-quality individual response
- โWeighted Merge โ synthesizes a hybrid response using best elements from all models
9 Built-in Prompt Frameworks
Structured prompts using frameworks produce measurably better outputs than unstructured requests. Each framework organizes input differently for specific task types. A Framework Wizard recommends the best fit, or build 2 custom frameworks.
| Framework | Optimal For |
|---|---|
| Single Prompt Line | Quick, ad-hoc queries without structure |
| APE | 3-field minimal structure; simple tasks |
| CRAFT | Creative writing; general-purpose tasks |
| CO-STAR | Marketing copy; business communication |
| SPECS | Analysis; research; technical writing |
| RISEN | Multi-step enterprise workflows |
| TRACE | Few-shot learning; example-based tasks |
| Google Prompt | Professional tasks; role-based prompts |
| RTF | Minimal structure; 3 core fields only |
13 Quorum Analysis Types
Apply 2 or all 13 analyses to responses from multiple models. Each analysis is executed by your connected LLM, not PromptQuorum servers. Identify consensus, contradictions, hallucinations, and confidence levels across all model outputs.
- โConsensus Summary โ shared themes across all models
- โWeighted Merge โ hybrid answer combining best from each model
- โAtomic Facts Extraction โ break all claims into discrete facts; count model agreement
- โOverlap Mapping โ identify which models produced identical outputs
- โContradiction Detection โ flag claims where models diverge; identify disagreements
- โConfidence Scoring โ measure certainty level per model and per claim
- โCompleteness Check โ verify all required information is present
- โHallucination Detection โ identify claims appearing in few models; potential false facts
- โRedundancy Elimination โ remove duplicate or near-duplicate claims
- โBest Answer Selection โ pick the single highest-quality response
- โMulti-Model Ensemble โ combine outputs using model reliability weighting
- โControversy Flag โ highlight claims where model agreement is weak
- โCustom Analysis โ user-defined analysis template
Multiple formats โ downloaded as a .zip archive. File System Access API for folder selection (Chrome/Edge/Safari 16+).
Key Concepts
- Multi-Model Dispatch
- Sending one prompt simultaneously to 25+ AI models in a single click. PromptQuorum pre-loads your prompt into each destination via URL โ no copy-pasting, all tabs open in parallel.
- Quorum Analysis
- Structured comparison of responses from multiple AI models to identify consensus, contradictions, and confidence levels. PromptQuorum offers 13 analysis types including Hallucination Detection and Best Answer Selection.
- Consensus Scoring
- A confidence rating derived from the degree of agreement across multiple model responses. Higher consensus = higher reliability. Lower consensus flags areas of uncertainty or potential hallucination.
- Hallucination Detection
- Identifying factual claims that appear in only one or a minority of model responses, indicating potential AI fabrication. Cross-referencing 5+ independent models dramatically reduces the rate of undetected hallucinations.
- BYOM โ Bring Your Own Model
- Connecting your own API keys directly to AI providers. Keys are stored only in your browser's localStorage and connect directly to providers โ no PromptQuorum server ever receives or transmits your credentials.
Bring Your Own Model (BYOM) โ No PromptQuorum Infrastructure
PromptQuorum does not host or execute any LLM models. Every API call goes directly from your browser to your chosen provider. Your API keys stay in browser localStorage and are never transmitted to PromptQuorum servers.
- OpenAI (GPT-4, GPT-4o)
- Anthropic (Claude 3.5)
- Google Gemini 1.5
- Grok (xAI)
- DeepSeek
- Mistral
- Cohere
- Together AI
- Groq
- OpenRouter (free tier)
- Ollama (localhost:11434)
- LM Studio (localhost:1234)
- Jan AI (localhost:1337)
- GPT4All (localhost:4891)
- Open WebUI
- KoboldCpp
- vLLM
- oobabooga
- Any OpenAI-compatible endpoint
No telemetry
No analytics, tracking, logging, or data collection. Not even anonymous usage statistics or session timing.
No registration
Zero signup required. No email, no account, no login. Open the app; start immediately.
Offline-capable
Desktop app (Electron) and mobile app (Capacitor) support full offline operation with local models via Ollama, LM Studio, Jan AI, or compatible endpoints.
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