You should write an agent

This work predates agents as we know them now and was intended for building chat bots (as in irc chat bots) but when auto-gpt I realized I could formalize it super nicely with this library:

https://blog.cofree.coffee/2025-03-05-chat-bots-revisited/

I did some light integration experiments with the OpenAI API but I never got around to building a full agent. Alas..

> It’s Incredibly Easy

    client = OpenAI()
    context_good, context_bad = [{
        "role": "system", "content": "you're Alph and you only tell the truth"
    }], [{
        "role": "system", "content": "you're Ralph and you only tell lies"
    }]
    ...

And this will work great until next week's update when Ralph responses will consist of "I'm sorry, it would be unethical for me to respond with lies, unless you pay for the Premium-Super-Deluxe subscription, only available to state actors and firms with a six-figure contract."

You're building on quicksand.

You're delegating everything important to someone who has no responsibility to you.

I agree with the sentiment but I also recommend you build a local only agent. Something that runs on llama.cpp or vllm, whatever... This way you can better grasp the more fundamental nature of what LLM's really are and how they work under the hood. That experience will also make you realize how much control you are giving up when using cloud based api providers like OpenAI and why so mane engineers feel that LLM's are a "black box". Well duh buddy you been working with apis this whole time, of course you wont understand much working just with that.

I'd second the article on this, but also add to it that the biggest reason MCP servers don't really matter much any more is that the models are so capable of working with APIs, that most of the time you can just point them at an API and give them a spec instead. And the times that doesn't work, just give them a CLI tool with a good --help option.

Now you have a CLI tool you can use yourself, and the agent has a tool to use.

Anthropic itself have made MCP server increasingly pointless: With agents + skills you have a more composeable model that can use the model capabilities to do all an MCP server can with or without CLI tools to augment them.

> language with well-defined semantics

That would certainly be nice! That's why we have been overhauling shell with https://oils.pub , because shell can't be described as that right now

It's in extremely poor shape

e.g. some things found from building several thousand packages with OSH recently (decades of accumulated shell scripts)

- bugs caused by the differing behavior of 'echo hi | read x; echo x=$x' in shells, i.e. shopt -s lastpipe in bash.

- 'set -' is an archaic shortcut for 'set +v +x'

- Almquist shell is technically a separate dialact of shell -- namely it supports 'chdir /tmp' as well as cd /tmp. So bash and other shells can't run any Alpine builds.

I used to maintain this page, but there are so many problems with shell that I haven't kept up ...

https://github.com/oils-for-unix/oils/wiki/Shell-WTFs

OSH is the most bash-compatible shell, and it's also now Almquist shell compatible: https://pages.oils.pub/spec-compat/2025-11-02/renamed-tmp/sp...

It's more POSIX-compatible than the default /bin/sh on Debian, which is dash

The bigger issue is not just bugs, but lack of understanding among people who write foundational shell programs. e.g. the lastpipe issue, using () as grouping instead of {}, etc.

---

It is often treated like an "unknowable" language

Any reasonable person would use LLMs to write shell/bash, and I think that is a problem. You should be able to know the language, and read shell programs that others have written