claude-code-tools

Amusingly, for a library [1] I’ve been building, 100% of the code is AI-written (with a huge number of iterations of course) and the ONLY part I wanted to write myself is the portion of the README that explains the thought process behind one of the features. It took a lot of thinking and iterations to come up with the right style and tone, and methodically explain the ideas in the right order. Leaving that to an LLM would have been a frustrating exercise. [1] https://github.com/pchalasani/claude-code-tools

I like that it does not require following any particular "system" or discipline. But having to use a non-local/proprietary memory layer is not ideal. My own fully-local, minimalistic take on this problem of "session continuation without compaction" is to rely on the session JSONL files directly rather than create separate "memory" artifacts, and seamlessly index them to enable fast full-text search. This is the idea behind the "aichat" command-group + plugin I just added to my claude-code-tools [1] repo. You can quit your Claude-Code/Codex-CLI session S and type aichat resume <id-of-session-S-you-just-quit> It launches a TUI, offering a few ways to continue your work: - blind trim - clones the session, truncates large tool calls/results and older assistant messages, which can clear up as much as 50% of context depending of course on

You mean so-called headless or non-interactive mode? Yes I’ve considered that but the advantage communication via Tmux panes is that all agent work is fully visible and you can intervene as needed. My repo has other tools that leverage such headless agents; for example there’s a resume [1] functionality that provides alternatives to compaction (which is not great since it always loses valuable context details): The “smart-trim” feature uses a headless agent to find irrelevant long messages for truncation, and the “rollover” feature creates a new session and injects session lineage links, with a customizable extraction of context for the task to be continued. [1] https://github.com/pchalasani/claude-code-tools?tab=readme-o...

This resonates with how I’ve been thinking about open source. I see the steps as: 1. Personally identify a pain in your own work, and it most likely will be a pain for many others. 2. Build a solution to solve for it. 3. Organically talk about it in forums — for me this is Reddit, HN lately and to some extent Bluesky. When people ask why I build open source, I say it’s about signaling. As other comments have mentioned, if you’re fortunate enough that it gains traction, it becomes your calling card and can lead to consulting and jobs. It’s analogous to academic publishing (used to do more of that) but with different dynamics. My personal examples of solving for a pain are: [A] I started building the Langroid LLM agent framework after having a look at LangChain in Apr 2023, at a time when there was hardly any talk of LLM-agents. The aim was

A workflow I find useful is to have multiple CLI agents running in different Tmux panes and have one consult/delegate to another using my Tmux-CLI [1] tool + skill. Advantage of this is that the agents’ work is fully visible and I can intervene as needed. [1] https://github.com/pchalasani/claude-code-tools?tab=readme-o...

I recently found myself wanting to use Claude Code and Codex-CLI with local LLMs on my MacBook Pro M1 Max 64GB. This setup can make sense for cost/privacy reasons and for non-coding tasks like writing, summarization, q/a with your private notes etc. I found the instructions for this scattered all over the place so I put together this guide to using Claude-Code/Codex-CLI with Qwen3-30B-A3B, 80B-A3B, Nemotron-Nano and GPT-OSS spun up with Llama-server: https://github.com/pchalasani/claude-code-tools/blob/main/do... Llama.cpp recently started supporting Anthropic’s messages API for some models, which makes it really straightforward to use Claude Code with these LLMs, without having to resort to say Claude-Code-Router (an excellent library), by just setting the ANTHROPIC_BASE_URL.