6 ms·
Show HN: Axe – A 12MB binary that replaces your AI framework
I built Axe because I got tired of every AI tool trying to be a chatbot.
Most frameworks want a long-lived session with a massive context window doing everything at once. That's expensive, slow, and fragile. Good software is small, focused, and composable... AI agents should be too.
Axe treats LLM agents like Unix programs. Each agent is a TOML config with a focused job. Such as code reviewer, log analyzer, commit message writer. You can run them from the CLI, pipe data in, get results out. You can use pipes to chain them together. Or trigger from cron, git hooks, CI.
What Axe is:
- 12MB binary, two dependencies. no framework, no Python, no Docker (unless you want it)
- Stdin piping, something like `git diff | axe run reviewer` just works
- Sub-agent delegation. Where agents call other agents via tool use, depth-limited
- Persistent memory. If you want, agents can remember across runs without you managing state
- MCP support. Axe can connect any MCP server to your agents
- Built-in tools. Such as web_search and url_fetch out of the box
- Multi-provider. Bring what you love to use.. Anthropic, OpenAI, Ollama, or anything in models.dev format
- Path-sandboxed file ops. Keeps agents locked to a working directory
Written in Go. No daemon, no GUI.
What would you automate first?
- deleted 7mo ago[deleted]
- armcat 7mo agoGreat work! Kind of reminds me of ell (https://github.com/MadcowD/ell https://github.com/MadcowD/ell), which had this concept of treating prompts as small individual programs and you can pipe them together. Not sure if that particular tool is being maintained anymore, but your Axe tool caters to that audience of small short-lived composable AI agents.
- jrswab 7mo agoThanks for checking it out! And yes the tool is indeed catering to that crowed. It's a need I have and thought others could use it as well.
- a1o 7mo agoIs the axe drawing actually a hammer?
- fortyseven 7mo agoSure is. How weird.
- hundchenkatze 7mo agoLooks like an axe to me. The cutting edge of the axe is embedded into the surface. And the handle attaches near the back of the head like an axe. Most hammers I've seen the handle attaches in the middle.
- parineum 7mo agoThere are many different styles of axe and some don't flair out much. [0]https://inchbyinch.de/wp-content/uploads/2017/08/0400-axe-types.jpeg https://inchbyinch.de/wp-content/uploads/2017/08/0400-axe-ty... [1]https://i.pinimg.com/originals/da/14/80/da148078cc1478ec6b255d3f5583e2a3.jpg https://i.pinimg.com/originals/da/14/80/da148078cc1478ec6b25...
- devmor 7mo agoI believe it's actually trying to render a splitting maul, which people often confuse for an axe.
- daveguy 7mo agoSplitting mauls have a wider angle to help separate wood pieces and a beefier back to use with/as a sledgehammer or splitting wedge. What's rendered is definitely more like an axe than a splitting maul.
- nthypes 7mo agoThere is no "session" concept?
- jrswab 7mo agoNot yet but is on the short list to implement. What would you need from a session for single purpose agents? I'm seeing it more as a way to track what's been done.
- mark_l_watson 7mo agoIf I have time I want to try this today because it matches my LLM-based work style, especially when I am using local models: I have command line tools that help me generated large one-shot prompts that I just paste into an Ollama repl - then I check back in a while. It looks like Axe works the same way: fire off a request and later look at the results.
- jrswab 7mo agoExactly! I also made it to chain them together so each agent only gets what it needs to complete its one specific job.
- punkpeye 7mo agoWhat are some things you've automated using Axe?
- jrswab 7mo agoI have a few flows I'm using it for and have a growing list of things I want to automate. Basically, if there is a process that takes a human to do (like creating drafts or running scripts with variable data) I make axe do it. 1. I have a flow where I pass in a youtube video and the first agent calls an api to get the transcript, the second converts that transcript into a blog-like post, and the third uploads that blog-like post to instapaper. 2. Blog post drafting: I talk into my phone's notes app which gets synced via syncthing. The first agent takes that text and looks for notes in my note system for related information, than passes my raw text and notes into the next to draft a blog post, a third agent takes out all the em dashes because I'm tired of taking them out. Once that's all done then I read and edit it to be exactly what I want.
- bensyverson 7mo agoIt's exciting to see so much experimentation when it comes to form factors for agent orchestration! The first question that comes to mind is: how do you think about cost control? Putting a ton in a giant context window is expensive, but unintentionally fanning out 10 agents with a slightly smaller context window is even more expensive. The answer might be "well, don't do that," and that certainly maps to the UNIX analogy, where you're given powerful and possibly destructive tools, and it's up to you to construct the workflow carefully. But I'm curious how you would approach budget when using Axe.
- jrswab 7mo ago> how you would approach budget when using Axe Great question and it's something that I've not dig into yet. But I see no problem adding a way to limit LLMs by tokens or something similar to keep the cost for the user within reason.
- ufish235 7mo agoWhy is this comment an ad?
- ForceBru 7mo agoThis is the OP promoting their project — makes sense to me
- stronglikedan 7mo agoHow can it be an ad if it's not selling anything? Seems like a proud parent touting their child to me.
- jrswab 7mo agoI am pretty proud of this one :)
- zrail 7mo agoIt's a Show HN. That's the point.
- lovich 7mo agoBecause they had an AI write it. Their other comments seem organic but the one you’re responding to does not
- jedbrooke 7mo agolooks interesting, I agree that chat is not always the right interface for agents, and a LLM boosted cli sometimes feels like the right paradigm (especially for dev related tasks). how would you say this compares to similar tools like google’s dotprompt? https://google.github.io/dotprompt/getting-started/ https://google.github.io/dotprompt/getting-started/
- jrswab 7mo agoI've not heard of that before but after looking into it I think they are solving different problems. Dotprompt is a promt template that lives inside app code to standardize how we write prompts. Axe is an execution runtime you run from the shell. There's no code to write (unless you want the LLM to run a script). You define the agent in TOML and run with `axe run <agent name> and pipe data into it.
- ozgurozkan 7mo ago[flagged]
- Lliora 7mo ago12MB for an "AI framework replacement"? That's either brilliant compression or someone's redefining "framework" to mean "toy model that works on my laptop." Show me the benchmarks on actual workloads, not the readme poetry.
- jrswab 7mo agoThis is not an LLM but a Binary to run LLMs as single purpose agents that can chain together.
- mrweasel 7mo agoYeah I was disappointed by that too.
- deleted 7mo ago[deleted]
- longtermemory 7mo ago[dead]
- hrmtst93837 7mo ago[flagged]
- 0xbadcafebee 7mo agoNice. There's another one also written in Go (https://github.com/tbckr/sgpt https://github.com/tbckr/sgpt), but i'll try this one too. I love that open source creates multiple solutions and you can choose the one that fits you best
- jrswab 7mo agoThanks! Looks like sgpt is a cool tool. Axe is oriented around automation rather than interaction like sgpt. Instead of asking something you define it once and hook it into a workflow.
- zrail 7mo agoLooks pretty interesting! Tiny note: there's a typo in your repo description.
- jrswab 7mo agonooo! lol but thanks, I'll go hunt it down.
- TSiege 7mo agoThis looks really interesting. I'm curious to learn more about security around this project. There's a small section, but I wonder if there's more to be aware of like prompt injection
- jrswab 7mo agoI'm happy you brought this up. I've been thinking about this and working on a plan to make it as solid as possible. For now, the best way would be to run each agent in a docker container (there is an example Dockerfile in the repo) so any destructive actions will be contained to the container. However, this does not help if a person gives access to something like Google Calendar and a prompt tells the LLM to be destructive against that account.
- saberience 7mo agoI’m having trouble understanding when/where I would use this? Is this a replacement for pi or codex?
- jrswab 7mo agoThis is not a replacement for either in my opinion. Apps like codex and pi are interactive but ax is non-interactive. You define an agent once and the trigger it however you please.
- Orchestrion 7mo agoThe Unix-style framing resonates a lot. One thing I’ve noticed when experimenting with agent pipelines is that the “single-purpose agent” model tends to make both cost control and reasoning easier. Each agent only gets the context it actually needs, which keeps prompts small and behavior easier to predict. Where it gets interesting is when the pipeline starts producing artifacts instead of just text — reports, logs, generated files, etc. At that point the workflow starts looking less like a chat session and more like a series of composable steps producing intermediate outputs. That’s where the Unix analogy feels particularly strong: small tools, small contexts, and explicit data flowing between steps. Curious if you’ve experimented with workflows where agents produce artifacts (files, reports, etc.) rather than just returning text.
- jrswab 7mo ago> Curious if you’ve experimented with workflows where agents produce artifacts (files, reports, etc.) rather than just returning text. Yes! I run a ghost blog (a blog that does not use my name) and have axe produce artifacts. The flow is: I send the first agent a text file of my brain dump (normally spoken) which it then searched my note system for related notes, saves it to a file, then passes everything to agent 2 which make that dump a blog draft and saves it to a file, agent 3 then takes that blog draft and cleans it up to how I like it and saves it. from that point I have to take it to publish after reading and making edits myself.
- Orchestrion 7mo agoThat’s a really nice pipeline. The “save to file between steps” pattern seems to appear very naturally once agents start doing multi-stage work. One thing I’ve noticed when experimenting with similar workflows is that once artifacts start accumulating (drafts, logs, intermediate reports, etc.), you start running into small infrastructure questions pretty quickly: – where intermediate artifacts live – how later agents reference them – how long they should persist – whether they’re part of the workflow state or just temporary outputs For small pipelines the filesystem works great, but as the number of steps grows it starts to look more like a little dataflow system than just a sequence of prompts. Do you usually just keep everything as local files, or have you experimented with something like object storage or a shared artifact layer between agents?
- let_rec 7mo agoIs there Gemini support?
- jrswab 7mo agoNot yet but it will be easy to add. If you need it can you create an issue in GitHub? I should be able to get that in today.
- dumbfounder 7mo agoNow what we need is a chat interface to develop these config files.
- btbuildem 7mo agoI really like seeing the movement away from MCP across the various projects. Here the composition of the new with the old (the ol' unix composability) seems to um very nicely. OP, what have you used this on in practice, with success?
- jrswab 7mo agoI've shared a few flows I use a lot right now in some other comments.
- hamandcheese 7mo ago> Each agent is a TOML config with a focused job. Such as code reviewer, log analyzer, commit message writer. You can run them from the CLI, pipe data in, get results out. I'm a bit skeptical of this approach, at least for building general purpose coding agents. If the agents were humans, it would be absolutely insane to assign such fine-grained responsibilities to multiple people and ask them to collaborate.
- hiccuphippo 7mo agoClankers are not humans.
- cweagans 7mo agoThis is the second time I've seen somebody use the word "clankers" in the last couple days to refer to AI. Is that a thing now? Where'd that come from? Gonna be honest, it has taken away from the message both times I've seen it. It feels a bit like you're LARPing your favorite humans vs robots tv show.
- JadeNB 7mo agoYou can find the answers to both of your questions on Wikipedia: https://en.wikipedia.org/wiki/Clanker https://en.wikipedia.org/wiki/Clanker
- anigbrowl 7mo agoIt is a thing, i've been hearing it for at least 6 months. There's a lot of people who really hate AI and want nothing to do with it.
- MisterTea 7mo agoI've been hearing the term in IRC and discords for about a year or more already. I get that it can seem childish but when you compare that to the indolent people who are demanding AI, it cancels out.
- jrop 7mo ago
- swaminarayan 7mo agoAxe treats LLM agents like Unix programs—small, composable, version-controllable. Are we finally doing AI the Unix way?
- reacharavindh 7mo agoReminded me of this from my bookmarks. https://github.com/chr15m/runprompt https://github.com/chr15m/runprompt
- creehappus 7mo agoI really like the project, although I would prefer a json5 config, not toml, which I find annoying to reason about.
- boznz 7mo agoI will give it a try, I like the idea of being closer to the metal. A Proper self-contained, self improving AI@home with the AI as the OS is my end goal, I have a nice high spec but older laptop I am currently using as a sacrificial pawn experimenting with this, but there is a big gap in my knowledge and I'm still working through GPT2 level stuff, also resources are tight when you're retired. I guess someone will get there this year the way things are going, but I'm happy to have fun until then.
- jrswab 7mo agoI'm excited to see how this plays out. Keep me updated on x(twitter)
- stpedgwdgfhgdd 7mo ago“ MCP support. Axe can connect any MCP server to your agents” I just don't see this in the readme… It is not in the Features section at least. Anyway, i have MCP server that can post inline comments into Gitlab MR. Would like to try to hook it up to the code reviewer.
- jrswab 7mo agoSorry, I need to update that. I just added MCP support a day or so ago.
- deleted 7mo ago[deleted]
- mccoyb 7mo agoCool work! Aside but 12 MB is ... large ... for such a thing. For reference, an entire HTTP (including crypto, TLS) stack with LLM API calls in Zig would net you a binary ~400 KB on ReleaseSmall (statically linked). You can implement an entire language, compiler, and a VM in another 500 KB (or less!) I don't think 12 MB is an impressive badge here?
- ipython 7mo agoit's written in golang. 12MB barely gets you "hello world" since everything is statically linked. With that in mind, the size is impressive.
- mccoyb 7mo agoI know off topic, but is that mostly coming from the Go runtime (how large is that about?)
- nuxi 7mo agogolang doesn't statically link everything by default (anymore?), this is from FreeBSD: $ ls -l axe -rwxr-xr-x 1 root wheel 12830781 Mar 12 22:38 axe* $ ldd axe axe: libthr.so.3 => /lib/libthr.so.3 (0xe2e74a1d000) libc.so.7 => /lib/libc.so.7 (0xe2e74c27000) libsys.so.7 => /lib/libsys.so.7 (0xe2e75de6000) [vdso] (0xe2e7366b000)
- emmanueloga_ 7mo agoThe excessive size of Go binaries is a common complain. I last recall seeing a related discussion on Lobsters [1]. Who knows, maybe the binary could be shrunk a bit? IMHO 12mb binary size is not that big of a deal. -- 1: https://lobste.rs/s/tzyslr/reducing_size_go_binaries_by_up_77 https://lobste.rs/s/tzyslr/reducing_size_go_binaries_by_up_7...
- nine_k 7mo ago12 MB is not large; it's like 3 minutes of watching YouTube. Actual RAM consumption is only very weakly correlated to the binary size, and that's what matters.
- Multicomp 7mo agoThis is what I've been trying to get nanobot to do, so thanks for sharing this. I plan to use this for workflow definitions like filesystems. I have a known workflow to create an RPG character with steps, lets automate some of the boilerplate by having a succession of LLMs read my preferences about each step and apply their particular pieces of data to that step of the workflow, outputting their result to successive subdirectories, so I can pub/sub the entire process and make edits to intermediate files to tweak results as I desire. Now that's cool!
- jrswab 7mo agoLove to hear it! Thanks for checking it out and feel free to put up an issue on GitHub if you have any ideas for improvements.
- avoutic 7mo agoWhere is the nanobot approach not working for you?
- Multicomp 7mo agoFor me its mostly that nanobot is very not stable, its only 0.1.4.post4 and who knows what software provenance it's got. Functionality that worked last week doesn't work this week (anecdote: I used to be able to do long tool chains and conversations back to back but after more recent updates, the tool seems to only do one tool write then report back that it's done more tool writings and I have to remind it to finish the job).
- eikenberry 7mo agoDoes it support the use of other OpenAI API compatible services like Openrouter?
- jrswab 7mo agoYes, I've used it with on OpenAI compatible API from an internal LLM at my job.
- eikenberry 7mo agoThanks!
- hmokiguess 7mo agolooks really cool, how does it differ from something like running claude headless with `claude -p`?
- jrswab 7mo agoYou don't have all the Claude Code overhead. It only gets what you give it.
- hmokiguess 7mo agowhat do you mean by that, not sure I understand
- snadal 7mo agoNice! I’ll try this soon, and I’m afraid I’ll end up using it a lot. @jrswab, do you think it would be feasible to limit outgoing connections to a whitelist of domains, URLs, or IP addresses? I’d like to automate some of my email, calendar, or timesheet tasks, but I’m concerned that a prompt injection could end up exfiltrating or deleting data. In fact, that’s the main reason why I’m not using Openclaw or similar projects with real data yet.
- jrswab 7mo agoYes, I think it will be quite trivial to make a output allow list. That's a great idea!
- longtermemory 7mo ago[dead]
- testingtrade 7mo agoamazing work my friend
- bmurphy1976 7mo agoThis is interesting. I'd be curious to see a bunch more working examples. Personally I like the chat model because I iterate heavily on planning specs and have a lot of back and forth before implementation. I could see using this once the plan is defined and switching back to chat while iterating on post-implementation cleanup and refactoring.
- anotherevan 7mo agoI really like this idea. Gonna need an "Awesome Axe" page that collects agents. One idea I'm thinking of is, after an agent has been in use for a while, and built up and understanding of the task, would be something like, "Write a Python script to replace this agent." I could imagine this would work with agents that are processing log files or other semi-structured data for example.
- CraigJPerry 7mo agoI've had good success with something along these lines but perhaps a bit more raw: - claude takes a -p option - i have a bunch of tiny scripts, each script is an agent but it only does one tiny task - scripts can be composed in a unix pipeline For example: $ git diff --staged | ai-commit-msg | git commit -F - Where ai-commit-msg is a tiny agent: #!/usr/bin/env bash # ai-commit-msg: stdin=git diff, stdout=conventional commit message # Usage: git diff --staged | ai-commit-msg set -euo pipefail source "${AGENTS_DIR:-$HOME/.agents}/lib/agent-lib.sh" SYSTEM=$(load_skills \ core/unix-output.md \ core/be-concise.md \ domain/git.md \ output/plain-text.md) SYSTEM+=$'\n\nTask: Given a git diff on stdin, output a single conventional commit message. One line only.' run_agent "$SYSTEM" And you can see to keep the agents themselves tiny, they rely on a little lib to load the various skills and optionally apply some guard / post-exec validator. Those validators are usually simple grep or whatever to make sure there were no writes outside a given dir but sometimes they can be to enforce output correctness (always jq in my examples so far...). In theory the guard could be another claude -p call if i needed a semantic instruction.
- avoutic 7mo agoI was looking at something similar. What does your agent-lib.sh look like?
- CraigJPerry 7mo agoSomething like this: https://github.com/craigjperry2/tiny-agents/blob/main/lib/agent-lib.sh https://github.com/craigjperry2/tiny-agents/blob/main/lib/ag...
- zahlman 7mo ago> 12MB binary, two dependencies. no framework, no Python, no Docker (unless you want it) Does it do anything CPU-bound on its own, such that it benefits significantly from being a compiled (Go) executable? I actually like having things like this done in Python, since there's more potential to hack around with them.
- tianrking 7mo ago[flagged]
- CuriouslyC 7mo agoWhy not just run your typical claude/codex/pi/etc with a prompt as the command line/input?
- rockmanzheng 7mo ago[dead]
- rellfy 7mo agoThis is a great concept. I fully agree with small, focused and composable design. I've been exploring a similar direction at asterai.io but focusing more on the tool layer than agent layer, with portable WASM components you write once in any language and compose together. I currently use Claude web with an MCP component for my workflows but axe looks like it could be a nicer and quicker way to work with the tools I have.
- uhx 7mo ago> - Path-sandboxed file ops. Keeps agents locked to a working directory How is it supposed to work, if agent can simply run "cat" command instead of using skill for file read/write/etc?
- linkregister 7mo agochroot
- uhx 7mo agoyou cant be serious chroot is not a security tool and never has been
- linkregister 7mo agofine. cgroups, pivot_root, whatever. this is a solved problem.
- multidude 7mo agoA problem i have is that the agent's mental model of the system im building diverges from reality over time. After discussing that many times and asking it to remember, it becomes frustrating. In the README you say the agents memory persists across runs, would that solve said problem? Also, I had to do several refactorings of my agent's constructs and found out that one of them was reinventing stuff producing a plethora of function duplications: e.g. DB connection pools(i had at least four of them simultaneously). Would AXE require shared state between chained agents? Could it do it if required?
- athrowaway3z 7mo agoI'm not sure if HN is being flooded with bots or if the majority of people here nowadays lack a sense of simplicity. Anybody looking to do interesting things should instantly ignore any project that mention "persistent memory". It speaks of scope creep or complexity obfuscation. If a tool wants to include "persistent memory" it needs to write the 3 sentence explanation of how their scratch/notes files are piped around and what it achieves. Not just claim "persistent memory". I might even go so far that any project using the terminology "memory" is itself doomed to spend too much time & tokens building scaffolding for abstractions that dont work.
- aa-jv 7mo ago>scaffolding The purpose of scaffolding is to create persistent memories. >claim "persistent memory" Just look at it as a build product. >abstractions that don't work Look at this as a testing problem.
- aa-jv 7mo agoThis is exactly what I have wanted for a while, so thank you very much! Disclaimer: I haven't dug into axe enough yet, just going on first impressions. >No daemon, no GUI. I love the world we developers live in right now. ;) >What would you automate first? In a sense, I have wanted to be able to just add AI to a repo, and treat it like the junior developer it is. Its okay if the junior developer will do literally any stupid thing I tell it to do, because I won't tell it to do stupid things. So, exactly: refactor this code, implement a shim, produce docs for <blah>, construct a build harness, write unit tests, produce a build, diff these codebases, implement this API, do all this on your own branch, and build and test things so that I can review the PR over coffee. Essentially, three word commands which will encourage the AI to produce better software. Through my repo, so I can just review through the repo. Okay, that's how I hope things work, now off to actually dig in to axe and give it a try on a few things, thanks very much again ..
- koakuma-chan 7mo agohttps://github.com/jrswab/axe/blob/master/internal/refusal/refusal.go https://github.com/jrswab/axe/blob/master/internal/refusal/r... Lmao
- ColonelPhantom 7mo agoI like the idea of LLM-calling as an automation-friendly CLI tool! However, putting all my agents in ~/.config feels antithetical to this. My Bash scripts do not live there either, but rather in a separate script collection, or preferably, at their place of use (e.g. in a repo). For example, let's say I want to add commit message generation (which I don't think is a great use of LLMs, but it is a practical example) to a repo. I would add the appropriate hook to /.git, but I would also want the agent with its instructions to live inside the repo (perhaps in an `axe` or `agents` directory). Can Axe load agents from the current folder? Or can that be added?
- paymenthunter01 7mo agoNice approach treating LLM agents like Unix programs. The TOML config per agent is clean. I've been working on something in a similar vein for invoice processing — small focused agents that do one thing well. Curious how you handle retries when an upstream LLM provider has intermittent failures mid-pipeline?
- bsoles 7mo agoI don't know exactly how these things work, but you may run into copyright/TM issues with Deque's Axe tool: https://www.deque.com/axe/devtools/ https://www.deque.com/axe/devtools/
- sameergh 7mo agoInteresting approach to slimming down the framework layer. One thing I've been thinking about as agents get lighter and faster the attack surface for prompt injection and behavioral drift grows. Are you thinking about any security primitives at this layer?
- uchibeke 7mo agoOk. this is interesting. How're you handling guardrails or the agent going rouge or doing something unintended?
- BrianFHearn 7mo ago[flagged]
- agenticbtcio 7mo ago[dead]
- ashersopro 7mo agoI LOVE IT
- ashersopro 7mo ago[flagged]
- ashersopro 7mo ago[flagged]
- kwstx 7mo agoReally cool approach, I like the “Unix philosophy” for agents. Curious how you handle state persistence and chaining sub-agents when agents are depth-limited. Also, do you have any strategies for ensuring data consistency across runs, especially when multiple agents interact with the same files?
- spranab 7mo ago[dead]
- vanleeclark1 7mo agoReach out to the Best Crypto Recovery Agency Treqora, if you want to get back your cryptocurrency from hackers , ponzi schemes, Investment platforms. Recover lost Bitcoins with Treqora.
- vanleeclark1 7mo agoI have been a victim of a bitcoin scam about 7 months back. Con artist gained access to my coinbase account through a phishing scam. They stole 2.8 BTC. I was really devastated. I did everything to get back my funds by contacting the support but there was nothing they could do. A friend of my told me about a recovery company name [Treqora. com] I wrote to them and They helped fight against various investment scams and I could only thank God they were able to retrieve my lost funds.
- Zetaphor 7mo agoHow do we report spam here?
- deleted 7mo ago[deleted]
- clearloop 7mo agoNice execution on the Unix pipes approach! Worth comparing architectures: Axe is stateless CLI (pipe in, get output), crabtalk.ai is daemon + commands (persistent process manages state, commands are standalone binaries on PATH). Both bet on small binaries (crabtalk is 8MB) and Unix philosophy, but the daemon gives you hot-swap, process isolation, and persistent state across invocations.