Alternatives
Products that do what Execute local prompts in SSH remote shells does
Instead of giving LLM tools SSH access or installing them on a server, the following command: $ promptctl ssh user@server makes a set of locally defined prompts "magically" appear within the remote shell as executable command line programs. For example, I have locally defined prompts for `llm-analyze-config` and `askai`. Then on (any) remote host I can: $ promptctl ssh user@host # Now on remote host $ llm-analyze-config /etc/nginx.conf $ cat docker-compose.yml | askai "add a load balancer" the prompts behind `llm-analyze-config` and `askai` execute on my local computer (even though…
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https://github.com/elijah-potter/ofc
2025 · elijahpotter.dev
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- 3GA
I was constantly googling CLI commands so I built this small CLI tool with GPT3. You can ask for shell commands right from the CLI. You'd need to use your own API KEY for this but it's pretty simple, instructions are in the README Not perfect but not bad either.
2022 · github.com
- 4LT
This is my take on the common "use llms to generate shell commands" utility. Emphasis is placed on good CLI UX, simplicity, and flexibility. `llm2sh` supports multiple LLM providers and lets LLMs generate multi-command sequences to handle complex tasks. There is also limited support for commands requiring `sudo` and other basic input. I recommend using Groq llama3-70b for day-to-day use. The ultra-low latency is a game-changer - its near-instant responses helps `llm2sh` integrate seamlessly into day-to-day tasks without breaking you out of the 'zone'. For more advanced tasks, swapping to…
2024 · github.com
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I built a single-file Python script that lets you run LLM prompts from the command line with templating, structured outputs, and the ability to chain prompts together. When I discovered Google's Dotprompt format (frontmatter + Handlebars templates), I realized it was perfect for something I'd been wanting: treating prompts as first-class programs you can pipe together Unix-style. Google uses Dotprompt in Firebase Genkit and I wanted something simpler - just run a .prompt file directly on the command line. Here's what it looks like: --- model: anthropic/claude-sonnet-4-20250514 output:…
Nov 2025 · github.com
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Bash4LLM is a single-file Bash wrapper for interacting with LLMs from the terminal. I created it because I wanted something simple that worked without installing Python, Node, or any other runtime. It uses only Bash, curl, and jq. You can send prompts, start a small chat, process files line by line, stream output, and save session metadata in JSON format. I tried to make it safe and predictable: no use of the system /tmp, no use of eval. Groq is supported by default, and other providers can be added with dedicated Bash scripts in the extras/providers/ folder. Example: echo…
Jun 2026 · github.com
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Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
2024 · jigsawstack.com
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Slupe lets you use web-based LLMs to modify local files without leaving the browser. npx slupe --clipboard It's a CLI tool that watches for LLM commands and executes them on your computer. Key features: - Custom syntax (NESL) designed for LLM reliability - fewer search/replace failures than existing approaches - Clipboard mode: copy from browser → Slupe executes → paste results back to clipboard - Generates instructions for LLMs based on your allowed actions - Sandboxed filesystem operations with configurable permissions + automatic git backups Motivation: I wanted to use web based Opus…
2025 · github.com
- 11LT
Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com
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I've been looking for a way to run LLMs safely without needing to approve every command. There are plenty of projects out there that run the agent in docker, but they don't always contain the dependencies that I need. Then it struck me. I already define project dependencies with mise. What if we could build a container on the fly for any project by reading the mise config? I've been using agent-en-place for a couple of weeks now, and it's working great! I'd love to hear what y'all think
Jan 2026 · github.com
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Jun 2026 · github.com
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Little tool that I made to understand how (un)reasonable my prompts are.
Jan 2026 · github.com
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We are excited to show Promptly (https://trypromptly.com), a prompt management platform for LLM apps that makes it easy to experiment, share and manage prompts in production. With Promptly, users can: - Try out different prompts and model parameters for various providers - Quickly share prompt snippets together with parameters and generated output. Think of it as CodePen or JSFiddle for prompts - Create high level endpoints on top of provider APIs (Open AI, DreamStudio etc) with templated and versioned prompts - Use built-in caching for endpoints that will help save on Open AI…
2023 · trypromptly.com
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Hi HN, I'm pleased to share Promptspot, an open-source (Apache License 2.0) project that helps automate testing of large language model (LLM) prompts against an array of input data. Modern LLMs offer an enormous amount of leverage if you "teach the bot to fish" — i.e. simply prompt it with both a "system prompt" (which typically doesn't change often) and a dynamic input, which is often application state, search results, recent activity, user profile data, etc. Existing playgrounds and prompt management systems often lack the rigor and flexibility required for this dynamic approach — and as…
2023 · github.com
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2024 · github.com
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Started this a few months ago because I wanted a better test runner for an entirely different LLM-based project, then got completely nerdsniped by making LLMs as easy as possible to hotswap into other projects. It's still on the early side but it's finally at the point where I would happily use it for my original project, so I figured I'd post it. It's also—almost by accident—fully remote compatible (permissioning system included!), so you can host it on a box and then connect a program to it remotely.
2023 · github.com
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Maybe some of you feel like me sometimes: I don't need SSH port forwarding very often. That's why I usually forget the exact ssh call by the time I need it. So that I no longer have to search for the correct call in the man page or on the Internet, I have implemented common scenarios interactively. Simply enter addresses, ports and user names and the result is the correct ssh call. I can simply copy it and use it.
2023 · github.com
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Hi! I've found myself repeatedly writing little scripts to do bulk calls to LLMs for various tasks. For example, run some analysis on a large list of records. There are a few "gotchas" to doing this. For example, some service providers have rate limits, and some models will not reliably return JSON (if you're asking for it). So, I've written a command for this. What I've tried to do here is let the user break up prompts and configuration as they see fit. For example, you can have a prompt file which includes the API key, rate limit, settings, etc. all together, or break these up into…
2025 · github.com
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Scan every LLM API call for PII and injection attacks
Jun 2026 · secure-mind-live.github.io
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