gidellav

Honestly it's better to have bad but fun ads than those sterile corporate design used nowadays.

What a bunch of slop: 182 top-level external dependencies (so, without considering nested dependencies) and 1318853 lines of code in Rust.

Building efficient agents is doable (I did it myself, github.com/gi-dellav/zerostack), companies just want to tokenmaxx, and as a by-product, produce and publish slop.

Sorry for self-insert, but that's exactly what I thought and I built https://github.com/gi-dellav/zerostack, so you are right I'd say

try lawyer help subreddits

I wrote a bunch of prompts for my own coding agent zerostack ( https://gi-dellav.github.io/zerostack/ ), and published a blogpost on our Prompts system ( https://rocketup.pages.dev/posts/alternative-to-skills/ ).

You can try to download the MD files from the source code https://github.com/gi-dellav/zerostack/tree/main/prompts and then load them into another coding agent

Actually, those two are different versions, but I am considering writing a full-length blog post on what changed in the last 2 weeks (aka: a lot).

Check what tools we already implemented, check your "slow" accusation, check the prompt system, check the provider integration (via Rig, so caching is already enabled), check the MCP support and other integrations that you don't even find on some major agents (git worktrees + loops).

For 3 years, your Lovable clone is something that Claude Code could make in a couple of days, but good luck shitting on other project I guess.

zerostack contains --sandbox flags that forces bwrap usage on all shell tool usage

Check https://news.ycombinator.com/item?id=48164948

This is actually a topic of current interest, and I think that I will switch to a sandbox-by-default once the bwrap implementation inside of zerostack is well tested and highly configurable.

Well... for the most part, you use it like skills, but instead of "commands" you can think of "environments": so '/prompt debug', which is one of the integrated prompts, allows for a debug-focused agent, you can then talk to it as a normal agent, and then '/prompt code' to go back to the standard coding agent.

About subagents: as of right now, the entire agent runs on one context buffer, so it doesn't support subagents in order to keep it lean; but there is a great chance that subagents will be added, as explore-heavy tasks often bloat the context window

I am currently deciding on adding ACP support or not (and ACP support should allow connections to JetBrains's IDEs)

Retry from Safari, sometimes it works better

Yes, I am open for PRs.

What you showed is a clear bug in my codebase, if you can, open a Github issue with each of your bugs.

Thanks!

Isn't 2 second startup time a lot? With zerostack, I managed to get it down to ~90ms

Exactly, this was my thought process when deciding if we should have Skills or not.

In the end, I think that this prompt-only design, with the integrated tools that come with zerostack, is more than enough.

I understand the concept, but I don't get what's the advantage over adding in the prompt instructions to use a specific bash command for a specific task, acting as a "custom tool".

Some interesting features I add on top of being lightweight are the prompts library, Git worktrees integration and Ralph Wiggum loops integrations.

1. I will add some screenshots tomorrow

2. As said before, there are no benchmarks right now, but it is good enough for me, so I hope it's good enough for y'all :)

3. Transfering settings from other agents is out-of-scope for a minimalstic coding agent, but the idea is that, apart from MCP server, the rest might just force you to learn how zerostack works, because of design choices such as not having Skills or having certain specialized tools integrated (worktrees and loops).

Hi, nice comment!

1. I had experience not only with wrong versions selected by the agents, but also weird crates (ex. choosing a crate with 10 github stars when a more complete and more supported one was available), reason why now I always choose the dependencies and then I let the agent work.

2. Yes, some of the provider code could be made using macros, I am just lazy... But thanks for the tip! I will save it for later.

3. No telemetry, and it can be checked thanks to the fact that there are no HTTP calls outside of the MCP implementation (via rmcp) and LLM connectors (via rig)

4. Yes, i set panic handler to 'abort', thinking that I would've get a nice size decrease: i yet have to experience a panic on this project, but I will revert it to default behavior if the binary size saving is really so small

5. While it is async, the entire project runs on one thread (as expressed in the main.rs with ```#[tokio::main(flavor = "current_thread")]```), as it allows for a nice ~8MB memory saving (so, 50% off) and no real performance loss, being such a simple tool.

---

P.S. Just switched back to default settings for panic handler

I get you, but when I decided to follow a no-skills approach (as in, no agent's Skills used), I had to decide what:

1. Couldn't be built only using prompts

2. Couldn't be built only using MCP servers

3. Would have improved my UX experience (as i hope, your UX experience).

From those three conditions, I chose integrated git worktrees and loops

I have to be honest and tell you that try to load such an heavy runtime as a scripting layer is not a great idea; at the same time I can tell you that I am working on another Rust project where I also needed scripting, and after three attempts I landed on rhai (https://rhai.rs/) (https://rhai.rs/book).

You might find it nice for pretty much all use cases except for high-performance scripting (so, if you are not try to build the entire logic entirely in rhai, you are going to be fine).

Thanks! I don't think that the only advantages are being open and lightweight, but you can actually find some more interesting features such as Ollama support, integrated Prompts (in order to compete with superpowers), git worktrees integration, and so on

Yes! This project derived from an OOM killer activation that happened on my old laptop beacuse i had more than 2 opencode instances open together with Firefox...

I actually though about this issue, but while Pi can have this script-like environment thanks to the fact that it's based on an interpreted language (TypeScript), Rust has its own limitation as a compiled language.

I decided to allow for customization in a different way:

1. The prompt library (~/.config/hypernova/prompts/) acts as a simpler alternative to Skills, with the built-in prompts that should replace superpowers + Claude's frontend-design

2. Compile-time features; things that might make the agent more bloated can be disabled when you decide to compile zerostack

3. Clean code; code that's short and easy to read, you can just throw zerostack on its own source code in order to build a custom fork if your necessity can't be satisfied. Good features could also be adopted by the main version.

4. Permission mode; as you can see in the README, there was lots of concern around the permission model, and I landed on a 4-mode system that goes from "Restrictive" (no commands) to "YOLO" (whatever the agent wants to do" + custom regex patterns for allow/ask/deny permission on 'bash' calls. In your case, you just need to run `zerostack -R` to force all tools to ask for permission.

(Also, there is a work-in-progress features for programmable agents, but that's yet to be announced)

While I think that the core philosohpy is the same, i'd like to ask: why adding features like Skills and prompt templates?

I personally decided to not implement Skills and instead using a prompt library approach, where certain .md are used to fully replace the system prompt, in order to allow for an approach similar to Skills with ~100 LoC dedicated to this system.

No problem, happy to help!

While I agree on the fact that it allows to manage resources efficiently, I don't agree on the fact the efficency derives from it being high-level; from a purely tecnical standpoint, i could skim off 2-3MB from the memory footprint by writing the code in pure C, as there are some unused parts of Rust's std that cannot be removed without recompiling std.

This is obv only a technical talk, as writing an AI TUI in pure C would be rather... ehhh

Hi! While I didn't try any agent benchmark, I already though of this possible issue, and I tried to approach it on two different levels:

1. The tools that are given to the agent are almost the same to the one defined in Opencode, except for Skills and Subagents (both features not implemented in zerostack)

2. Zerostack is prompt-based, so that it ships with a set of .md files, stored in ~/.config/zerostack/prompt, and that can be selected from the TUI in order to activate different 'agents': as you can see from the README, it is designed to contain the most important feautres of superpower + Claude's front-end design + git worktree support and Ralph Wiggum loops (both as integrated features)

Thanks! Funny enough, a good chunk of the coding was done by Deepseek v4 Flash, while I hand-wrote a couple of the TUI logic, as deepseek kept failing on certain cursor-moving logic, and I fully managed the memory optimization process (as you can read on another comment I left, it both a set of compiler optimizations and usage of certain Rust crates in order to leverage more efficient data structures).