Turn ideas into execution-ready context ready to run in agent builders like
, 
, 
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Vague chat prompts make models guess.
Prompt Context turns your ideas into structured, buildable context
Can you make me a cool app to take notes?
Maybe something like Notion but simpler.
I want it to look clean and fast.
Also maybe tags or something?
The model guesses what you meant. Every run feels random.
# App Context: Simple Notes
## Goal
Build a minimal note-taking web app to create,
edit, and tag notes.
## Requirements
- Add new notes with title and body
- Edit and delete existing notes
- Tag notes (multiple tags per note)
- Filter by tag
## Technical Details
- Frontend: React + Tailwind
- State: useState, persisted to localStorage
- Components: NoteInput, NoteList, TagFilter
- Data Model: { id, title, body, tags }
## Output
Generate React components and a main App.jsx
with routing ready.
The model builds with context — structured, reproducible, versioned.
“It's the first tool that treats context as code. Every change in Prompt Context is versioned and reversible, so I can finally move from prompt tinkering to full application logic.”
Peter
Startup PM
Refine, link, and version prompts as your ideas evolve — keeping every run consistent and every experiment grounded.
Explore how Prompt Context accelerates your workflow.
Structure faster. Align smarter. Ship with clarity.
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Prompt Context is like an IDE for context engineering — it lets you build, version, and link prompt logic as reusable context cards. Perfect for turning half-formed specs or messy notes into structured, executable context for agents, apps, or teams.
Prompt Context gives you:
Not yet — Prompt Context is currently designed for individual builders. Team workspaces and real-time collaboration are on the roadmap as we grow.
Yes. Start free with all the essentials for solo builders.
@Andibandi13 — I built this for myself after running into endless issues scaling side projects. If it helps you move faster or think better, that's the goal.
No. We use LLM APIs that don't retain or train on user inputs. Your context and generations stay private within your workspace.
Use it anywhere you build or orchestrate LLM-based apps: