prompt-x logoprompt-x

Prompt engineering platform · Early access

Prompts are the new code.
Manage them like code.

You've sent 3,000+ prompts last year, zero structure, zero versioning, just a few saved. It's time to do prompt engineering properly.

See how it works ↓
Code Review Agent · v4production
Anatomy

Role

Senior security code reviewer

Tone

Direct, constructive, technical

Context

Pull request · 847 lines · 12 files changed

Task

Review for security vulnerabilities, performance issues, and SOLID principle violations

Reasoning

chain-of-thought

Examples

3 examples attached

Output

Structured JSON · severity levels

Constraints

Critical and high-severity issues only

Tools

CodeSearch, GitBlame

Why do great prompts keep getting lost?

Most prompts are written once, buried in a Slack thread or Notion doc, and never found again. The ones that work — the ones that took 50 iterations — disappear with the project. prompt-x is the place for them.

Scattered across docs, Slack, Notion and code comments

Then a prompt clicks — where is it?

Manual reformatting every time you switch platforms

Claude needs XML, GPT wants Markdown.

No way to measure if a prompt is actually good

Quality should be numeric, not vibed.

What does a proper prompt engineering workflow look like?

prompt-x is a prompt engineering platform built around a semantic-fields anatomy to structure content, variables and versions to reuse and track content, and engines for generation, compilation and evaluation to improve the output.

5 target platforms

Write once, compile everywhere

Same prompt, perfect formatting. XML for Claude, Markdown for GPT, uppercase labels for Gemini. Switch platforms without re-editing.

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>

Simple · Standard · Advanced

Structure, not guesswork

Nine semantic fields — Role, Context, Task, and six more — guide every prompt. Consistent structure whether you write 3 fields or 9.

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...

Claude · ChatGPT · Gemini

One-click launch

Click 'Open in Claude' — your compiled prompt arrives pre-loaded in the right platform. Not copy-paste. 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>

~340 tokens · Optimized for ClaudeOpen in Claude →

Full version history

Every change, tracked

Timeline view, side-by-side compare, one-click restore. Draft → Testing → Production lifecycle with locked production versions.

Code Review Checklist

v7Currenttesting
+12 −32 hours ago
v6production
+5 −83 days ago
v5archived
+28 −141 week ago
CompareRestore

Auto-detection

Reusable prompts, dynamic values

Type {{customer_name}} and it's detected, highlighted, and autocompleted. Global variables shared across prompts.

Prompt Variables

{{company}}textprompt-x
{{user_name}}text—
{{output_lang}}selectEnglish

System Variables

{{current_date}}{{platform}}{{model}}

CLEAR framework

Quality you can measure

Built-in scoring across 5 dimensions — Clarity, Logic, Effectiveness, Adaptability, Robustness. Like a linter for your prompts.

82strong
Clarity
90
Logic
85
Effectiveness
78
Adaptability
80
Robustness
77

Browse · Filter · Search

Your full prompt library

Every prompt you've written. Status, version, score, and platform — all in one view.

Customer Support Agent
production92 · strongClaude
supportcustomer-facing
Code Review Checklist
testing78 · moderateGPT-4
engineeringreview

How does prompt-x work?

Structure your prompt using the proposed anatomy to improve the output, add variables for anything that changes between uses, compile for your target platform — Claude, Gemini, GPT, or Lovable — let the engines generate, refine, and evaluate, then launch in one click. Everything is versioned and stored for reuse.

1

Structure

Describe your intent. Choose 3, 5, or 9 fields. The anatomy guides your thinking.

2

Compile

Pick a platform. prompt-x formats your prompt — XML for Claude, Markdown for GPT, labels for Gemini.

3

Test & Refine

Score with CLEAR, compare versions side-by-side, iterate until every field is sharp.

4

Launch

One click. Your compiled prompt opens directly in Claude, ChatGPT, or Gemini. Pre-loaded. Ready.

Who is prompt-x built for?

+9

Semantic fields per prompt

+6

Latest models from main providers

5

Prompting frameworks (and 4 modes)

Coming soon: unlimited prompts, presets, API calls and endpoints — and much more.

Professional prompt engineering starts here.

Start free.

Frequently asked questions