prompt-xFeatures
Structure, compile, test, refine and launch — the full prompt engineering lifecycle in one platform.
What can prompt-x do?
01
Write once, compile for any AI platform.
One prompt, five formats. Claude expects XML tags. GPT expects Markdown headers. Gemini expects uppercase labels. Lovable expects natural prose. prompt-x compiles your canonical 9-field prompt into each format automatically.
Claude · GPT · Gemini · Lovable · Raw
Source
Role: Senior code reviewer
Tone: Direct, constructive
Task: Review the pull request for security vulnerabilities, performance issues...
Constraints: Focus on critical issues first
Compiled
Claude<role>
Senior code reviewer
</role>
<task>
Review the pull request for security vulnerabilities...
</task>
02
Nine semantic fields guide every prompt.
Role, Tone, Context, Task, Reasoning, Examples, Output Format, Constraints, and Tools. Each field answers a specific question about your prompt. Start with 3 fields (Simple) or use all 9 (Advanced).
Context engineering in practice
Role
Senior technical writer
Tone
Clear, precise, developer-friendly
Context
REST API with 47 endpoints, used by 3rd-party devs
Task
Generate API documentation with examples for each endpoint...
03
One-click launch to Claude, ChatGPT, and Gemini.
Click 'Open in Claude' and your compiled prompt opens pre-loaded in a new conversation. No copy-paste workflow. No manual formatting. Deployment, not distribution.
Zero-friction deployment
<role>
Senior code reviewer with 10+ years of experience
</role>
<task>
Review the following pull request. Focus on security vulnerabilities, performance bottlenecks, and adherence to SOLID principles.
</task>
<constraints>
Limit feedback to critical and high-severity issues only.
</constraints>
04
Every change tracked. Every version recoverable.
Timeline view shows the full history. Side-by-side compare highlights what changed. One-click restore to any version. And the status lifecycle — Draft → Testing → Production → Archived — gives prompts the same discipline as code.
Prompt engineering life-cycle
Code Review Checklist
05
Reusable prompts with dynamic values.
Type {{customer_name}} in any field — it's auto-detected, highlighted, and autocompleted. Define defaults, add descriptions, or import Global Variables shared across all your prompts.
Context engineering at scale
Prompt Variables
System Variables
06
Describe your intent. Get a structured prompt.
The AI Designer generates complete prompts from a natural language description — populating each field in the 9-field anatomy. The CLEAR Evaluator scores your prompt across 5 dimensions: Clarity, Logic, Effectiveness, Adaptability, Robustness.
Prompt agent with generation and evaluation skills
07
Your prompts, organized and searchable.
Grid and table views. Filter by status, platform, tags. Tabs for project-based grouping. Everything searchable. If you've written it, you can find it.
All-in-one prompt workspace
08
Prompts as infrastructure.
REST API for prompt retrieval. Generate API keys. Fetch compiled prompts by slug in the format your app needs. Production-status prompts accessible via API — your prompt library becomes deployment-ready infrastructure.
Coming in Pro+
curl \
-H "Authorization: Bearer px_sk_..." \
"https://api.prompt-x.io/v1/prompts/
customer-support-agent?format=claude"
{
"slug": "customer-support-agent",
"format": "claude",
"compiled": "<role>...</role>",
"version": "v7"
}
Frequently asked questions
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