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SPECIFICTION
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Promptimal

github.com

Linux
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Spec score 6.9 #23 of 28 in AI Prompt Generators

Spec sheet

What it does
Promptimal is a command-line tool that iteratively improves AI prompts using a genetic algorithm, without requiring a dataset.Read 9 Oct 2026 · github.com
Product
Promptimal is a command-line tool for improving AI prompts without needing a dataset.Read 9 Oct 2026 · github.com
License
The GitHub repository identifies the project as MIT licensed.Read 9 Oct 2026 · github.com
API requirement
The README says to add an OpenAI API key to the environment before using Promptimal.Read 9 Oct 2026 · github.com
Configuration
The number of iterations, candidate samples per iteration, and score threshold can be configured from the command line.Read 9 Oct 2026 · github.com
Current integrations
The README documents OpenAI API key configuration and does not describe other current provider integrations.Read 9 Oct 2026 · github.com
Custom evaluators
Users can supply a Python evaluator that accepts a prompt and returns a score between 0 and 1.Read 9 Oct 2026 · github.com
Default threshold
The README says the default stopping threshold is 1.0.Read 9 Oct 2026 · github.com
Evaluation
By default, an LLM evaluates candidate prompts using a self-consistency approach.Read 9 Oct 2026 · github.com
How to install
The README gives `pipx install promptimal` as the installation command.Read 9 Oct 2026 · github.com
How to start
Users can launch Promptimal in a terminal and enter a prompt and an improvement description, or provide them as command-line arguments.Read 9 Oct 2026 · github.com
Installation
The README gives `pipx install promptimal` as the installation command.Read 9 Oct 2026 · github.com
OpenAI setup
The README instructs users to set an OpenAI API key in their environment before running Promptimal.Read 9 Oct 2026 · github.com
Optimization
It uses a genetic algorithm to iteratively refine a prompt based on a description of what the user wants to improve.Read 9 Oct 2026 · github.com
Optimization controls
Command-line options control the number of iterations, candidate prompts per iteration, and score threshold for stopping.Read 9 Oct 2026 · github.com
Progress UI
The optimization process can be monitored in a UI opened in the terminal.Read 9 Oct 2026 · github.com
Provider roadmap
The README lists support for other LLM providers, including Anthropic, Groq, and Ollama, as roadmap items.Read 9 Oct 2026 · github.com
Roadmap
The roadmap lists support for other LLM providers, including Anthropic and Groq, and local models through Ollama, as planned work.Read 9 Oct 2026 · github.com
Terminal interface
After starting an optimization, users can monitor its progress in a UI in their terminal.Read 9 Oct 2026 · github.com

Where Specifiction places it

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