macOS menu bar · v1.1 · Apple Silicon + Intel

Every prompt is optimized in seven stages
before any model sees it.

PromptCraft lives in your menu bar and silently engineers every prompt through a 7 stage pipeline. The model receives structured intent, preserved entities, context from your active app, and a style specific final prompt. Local with Ollama or cloud with major providers, all from the same interface.

340% avg prompt clarity gain
<200ms pipeline overhead
7 optimization stages
Works with
Extensions
Under the hood

The pipeline, in full.

Scroll to step through each stage. At 01 and 07 normal scrolling resumes.

01 / 07

Intent Decomposer

Parses what you actually meant, not what you typed.

Your raw input is tokenized and analyzed to extract the primary verb, subject, object, and desired outcome. Intent Decomposer distinguishes between imperative instructions ("build X"), exploratory questions ("how does Y work"), and creative briefs ("write Z in the style of"). This classification routes your request to the appropriate assembly strategy in stage 5.

input make a login endpoint with proper error handling
output intent: CREATE domain: backend-api subject: authentication-endpoint constraints: implied[security, error-handling, input-validation]
02 / 07

Entity Extractor

Locks every technical term so nothing gets paraphrased away.

Named entity recognition identifies and pins all domain-critical tokens: proper nouns, version numbers, library names, acronyms, quoted strings, and technical identifiers. These entities receive immutable flags so no downstream stage synonymizes, paraphrases, or drops them. What you named is what the model sees.

input write a test for the UserAuthService.login() method
output PINNED: [UserAuthService] [login()] type: class-ref, method-ref immutable: true scope: test-coverage
03 / 07

Complexity Classifier

Scores the request on four dimensions and routes accordingly.

Four orthogonal dimensions are scored 0–1: scope, depth, ambiguity, and technicality. The combined score selects one of 12 assembly strategies and determines how much context the Context Engine injects in stage 4. A casual request gets a different treatment than a deep expert-level task.

input explain how transformers work
output scope: 0.72 depth: 0.81 ambiguity: 0.38 technicality: 0.64 strategy: pedagogical-depth
04 / 07

Context Engine

Reads what you are working on and injects it silently.

The Context Engine reads the macOS accessibility layer to determine your active application and selected text, queries the local clipboard history ring for recent content, and applies domain priors derived from your style profile. All injected as structured annotations in the assembly buffer without you writing any of it manually.

input (active: Xcode, selection: 42 lines Swift, clipboard: UserDefaults key)
output context.lang = swift context.framework = swiftui context.recently_edited = UserDefaults context.scope = mobile-development
05 / 07

Prompt Assembler

Builds the final prompt from every upstream signal.

The Assembler takes classified intent, pinned entities, complexity score, and injected context and renders the final prompt using the active style template. Engineering adds role specification, constraint enumeration, format requirements, and test directives. Every template is composable, not static.

input pinned entities + intent + context + style=Engineering
output You are a senior iOS engineer. Task: refactor selected Swift code using SwiftUI best practices. Constraints: preserve UserDefaults key compatibility, add unit test stubs for each public method. Format: annotated code + change rationale.
06 / 07

Model Execution

Routes to your provider and streams back without delay.

The assembled prompt routes to your configured endpoint, local Ollama, or a cloud provider via PromptCraft Cloud. Responses stream token by token with timeout handling, retry on transient errors, and request deduplication handled automatically.

input assembled prompt to configured provider
output provider: Claude 3.5 Sonnet latency: 178ms to first token streaming: active @ 48 tok/s status: 200 OK
07 / 07

Post Processor

Strips model artifacts before output reaches you.

The raw response passes through format validation, artifact stripping, verbosity enforcement, and structural cleanup. The result lands in the output area with copy, export, and clear actions ready immediately.

input raw model response with preamble + filler
output preamble: stripped format: validated verbosity: enforced output: ready to copy
Why it works

The AI already has your context.
You just don't have to write it.

context-engine.log
active_app = Xcode.app
lang = swift
framework = swiftui
selected_lines = 42
clipboard[0] = UserDefaults.standard.string(forKey:)
clipboard[1] = @AppStorage("onboarding_done")
scope = mobile-dev · ios-engineering
style_profile = Engineering
injected into assembler
01

Context you never have to write.

The Context Engine reads your active application, selected text, and clipboard history before assembling any prompt. Coding in Xcode with a SwiftUI file open? It knows. Writing in Notion? It adjusts tone. The pipeline always knows what you were working on — without you ever saying it.

Active app and language detected automatically
Clipboard history ring (last 8 items)
Accessibility permission is read-only, sandboxed
02

Seven optimization styles. Immediately.

Engineering adds role specification, constraint enumeration, format requirements, and test stubs. Research adds academic framing and source awareness. Content adds narrative structure and audience tone. You switch styles with one click — and the same rough input produces a completely different, equally precise result.

7 built-in styles: General, Engineering, Research, Content, Analysis, Academic, Creative
Custom templates you define, save, and reuse
Same input, different style = completely different optimized output
You type

write a test for the login method

Engineering

You are a senior backend QA engineer. Task: write an integration test suite for the login endpoint. Constraints: Jest, supertest, test success (200), bad credentials (401), rate limit (429), locked account (423)...

General

Write a comprehensive test for the login function covering the happy path and at least three failure scenarios with appropriate assertions...

140ms avg pipeline end-to-end
0 external servers before your AI
Local full Ollama support, offline capable
1 permission required (Accessibility, read-only)
03

Faster than you can blink. Private by design.

The entire 7-stage pipeline runs on your Mac in under 200ms. Your prompts never reach an external server until they touch your chosen AI provider — and with Ollama, that never happens at all. One read-only Accessibility permission. No telemetry. No logging. No account required for the app itself.

Zero telemetry, not even anonymous usage data
Signed with Developer ID, notarized by Apple
Works fully offline with any Ollama model
04

A second brain that learns your work.

Every optimization is embedded locally using Apple's NaturalLanguage framework and stored in a private SQLite database on your Mac. Over time, PromptCraft builds a semantic map of your projects, technical vocabulary, and working patterns. Future prompts automatically retrieve the most relevant past context and inject it into the assembly stage without you writing a single word of background.

On-device embeddings, no API call, no cloud sync
Project clusters named by entity frequency, not random IDs
Stores persons, projects, environments, technical terms
Up to 1,000 context entries, relevance threshold filtering
memory.clusters
cluster · friend-surf142 entries
cluster · promptcraft89 entries
cluster · swiftui-mobile56 entries
embedding = NL on-device · 512-dim
retrieval = cosine ≥ 0.65
3 relevant entries injected
Inline overlay Select text in any app. PromptCraft replaces it with the optimized version instantly. Xcode, VS Code, Notes, anywhere.
Watch folder Drop a .txt file into a watched folder. PromptCraft detects it, optimizes it, and copies the result to your clipboard automatically.
Local API REST endpoint on port 9847 with bearer token auth. Any tool, script, or workflow can trigger optimization via a single POST call.
Alfred workflow Type pc your prompt in Alfred. The optimized result copies to clipboard. Full workflow file included in the download.
05

Works in every app, not just PromptCraft.

The menu bar popover is the main interface. But PromptCraft also runs an inline overlay that intercepts selected text in any macOS application, a watch folder that processes files on drop, a local REST API for scripting and workflows, and an Alfred workflow for keyboard-first users. Wherever you write, PromptCraft can reach it.

Desktop window mode for distraction-free editing
Configurable delay and excluded app list for inline overlay
Rate limited local API, 10 requests per minute
06

Export to every tool you already use.

An optimized prompt is only valuable if it reaches the right destination. PromptCraft copies output as plain text, Markdown, Claude XML, or ChatGPT format. It also exports directly as a .cursorrules file for Cursor, a Claude Project system prompt, a ChatGPT Custom Instructions file, or a GitHub Issue. One optimized result, seven different delivery formats.

Copy for Claude, ChatGPT, GitHub Issue, Markdown, plain text
Save as .cursorrules, Claude Project Instructions, or ChatGPT Custom Instructions
Explain mode shows exactly why the output changed from the input
Diff view highlights every word the pipeline added or changed
Copy as Plain Text
Copy as Markdown
Copy for Claude (XML)
Copy for ChatGPT
Copy for GitHub Issue
Save as .cursorrules
Claude Project Instructions
ChatGPT Custom Instructions

"I got tired of starting every AI conversation with a three-paragraph context dump. I was spending more time writing the setup than writing the actual work. PromptCraft started as a one-file Swift script. When it started saving me forty minutes a day, I turned it into a real app."

Oguzhan Atalay @oguzhnatly · Lisbon, Portugal
265 GitHub stars on flutter_carplay 12+ products shipped 5+ years full-stack engineering
2024 Q1

First prototype — a menu bar app that prepended a role prompt to every request. One file of Swift. Worked immediately.

2024 Q2

Added the style selector and context engine. Response quality was obviously better. Started showing it to other engineers.

2024 Q4

Full 7-stage pipeline, clipboard history, and the cloud proxy for provider routing without API key management.

2025

Published. Still the only AI tool I actually keep open. Used every day, built on ever since.

Pricing

$99 once.
No annual renewal trap.

Pro is a one-time purchase. You own it, it updates forever, and you never get an invoice again. Cloud adds managed AI routing for people who don't want to manage API keys.

Pro

One-time · owns forever

Most popular
$99
one-time payment USD · no tax in most countries
Buy Pro — $99
  • All 7 pipeline stages, every request
  • Runs fully local — no data leaves your Mac
  • 7 built-in optimization styles General, Engineering, Research, Content, Analysis, Academic, Creative
  • Custom style templates Define and save your own prompt architecture
  • Unlimited clipboard history Every prompt and result stored locally, searchable
  • Any Ollama model (local, offline) llama3.2, mistral, deepseek, phi-3, qwen, and every future model
  • Global keyboard shortcut Cmd+Shift+Space from any app, any window, any Space
  • Activate on up to 3 Macs
  • All future updates
Cloud

Monthly · cancel any time

$12
per month no lock-in · cancel in settings
Start Cloud — $12/mo
  • Everything in Pro
  • Cloud routing: Claude, GPT-4o, Gemini No API key required
  • DeepSeek V3 and Mistral Large
  • Priority response queue
  • Activate on up to 5 Macs
  • Cancel any time
30-day full refund on Pro, no questions. Email hello@promptcraft.app with your order number.

Stop writing context.
Start getting answers.

macOS 14 Sonoma or later. Apple Silicon and Intel. 14-day free trial. No account, no credit card, no setup. License key by email after purchase.