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, Level of Detail, 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 Engineer
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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