jacob019

Just make sure you have the deps installed and add it to CC as a stdio mcp server. Tested on Linux only. I use it daily.

I'll add a new repo for it, maybe this evening, and I'll reply here with a link.

Git as db is clever, and the sqlite cache is nice. I'd been sketching sqlite based memory features myself. So much of the current ecosystem is suboptimal just because it's new. The models are trained around immutable conversation ledgers with user/tool/assistant blocks, but there are compelling reasons to manipulate both sides at runtime and add synthetic exchanges. Priming with a synthetic failure and recovery is often more effective than a larger, more explicit system message. Same with memory, we just haven't figured out what works best.

For code agents specifically, I found myself wanting old style completion models without the structured turn training--doesn't exist for frontier models. Talking to Claude about its understanding of the input token stream was fascinating; it compared it to my visual cortex and said it'd be unreasonable to ask me to comment on raw optic nerve data.

"Tell it to reread it again"-exactly the problem. My bookkeeping/decision engine has so much documentation I'm running out of context, and every bit is necessary due to interconnected dependencies. Telling it to reread content already in the window feels wrong, that's when I refine the docs or adjust the framework. I've also found myself adding way more docstrings and inline docs than I'd ever write for myself. I prefer minimal, self-documenting code, so it's a learning process.

There's definitely an art to prompts, and it varies wildly by model, completely different edge cases across the leading ones. Thanks again for the tip; I suspect we'll see a lot of interesting memory developments this year.

See CodeAgent or subrepl.py if you're just interested in the REPL orchestration. I also have a Python REPL MCP server that works with CC. It isn't published, but I could share it by request.

My favorite part of code agent is the /repl command. I can drop into the REPL mid session and load modules, poke around with APIs and data, or just point Claude in the right direction. Sometimes a snippet of code is worth 1000 words.

The agent "boots up" inside the REPL. Here's the beginning of the system prompt:

  >>> help(assistant)

  You are an interactive coding assistant operating within a Python REPL.
  Your responses ARE Python code—no markdown blocks, no prose preamble.
  The code you write is executed directly.

  >>> how_this_works()

  1. You write Python code as your response
  2. The code executes in a persistent REPL environment
  3. Output is shown back to you IN YOUR NEXT TURN
  4. Call `respond(text)` ...

I also built a browser control plugin that puts Claude directly into the heart of a live browser session. It can inject element pickers so I can click around and show it what I'm talking about. It can render prototype code before committing to disk, killing the annoying build-fix loop. I can even SSH in from my phone and use TTS instead of typing, surprisingly great for frontend design work. Knocked out a website for my father-in-law's law firm (gresksingleton.com) in a few hours that would've taken 10X that a couple years ago, and it was super fun.

The big win: complexity. CC has been a disaster on my bookkeeping system, there's a threshold past which Claude loses the forest for the trees and makes the same mistakes over and over. Code agent pushes that bar out significantly. Claude can build new tools on the fly when it needs them. Gemini works great too (larger context).

Have fun out there! /end-rant

Check it out: https://github.com/jacobsparts/agentlib/blob/main/src/agentl...

The framework is all python, but I used C for this helper. It uses unprivileged user namespaces to mount an overlay and run an arbitrary command, then when the command finishes, it writes a tarball of edits, which I use to create a unified diff. The framework orchestrates it all transparently, but the helper itself could be used standalone. Here's a short document about the sandbox in the context of it's use in my project:

https://github.com/jacobsparts/agentlib/blob/main/docs/sandb...

I also have a version that uses SUID instead of unprivileged user namespaces, available by request.

I often use claude code with --dangerously-skip-permissions but every once in a while it bites me. I've learned to use git for everything and put instructions to always commit BEFORE writes in CLAUDE.md. Claude can go off the rails on harder bug fixes, especially if there are multiple rounds of context compacting, it can really screw things up. It usually honors guidance not to modify outside of the project, but a simple sandbox adds so much, after the session is over you can see what changed and decide what to do with it. It really helps with the problem where it makes unexpected changes to the codebase, which you might not even notice otherwise, which can introduce serious bugs. The permission models of all the coding agents are rough--either you can't get anything done, or you throw caution to the wind. Full sandboxes are quite restrictive, which is why I rolled by own. Honestly your best option right now is just to have good version control and run coding agents in dedicated environments.

This is from DuckDuckGo's privacy policy: "We don’t track you. That’s our Privacy Policy in a nutshell. We don’t save or share your search or browsing history when you search on DuckDuckGo or use our apps and extensions."

If the court compelled DuckDuckGo to log all searches, I would be equally concerned.