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Products that do what RTK — Rust Token Killer does
Save 89% of wasted tokens on your AI coding agent
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Scored 65.2% vs google's official 47.8%, and the existing top closed source model Junie CLI's 64.3%. Since there are a lot of reports of deliberate cheating on TerminalBench 2.0 lately (https://debugml.github.io/cheating-agents/), I would like to also clarify a few things 1. Absolutely no {agents/skills}.md files were inserted at any point. No cheating mechanisms whatsoever 2. The cli agent was run in leaderboard compliant way (no modification of resources or timeouts) 3. The full terminal bench run was done using the fully open source version of the agent, no…
Apr 2026 · github.com
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- 7CS
Coding agents don't have long-term memory. But you do have months of full-fidelity agent transcripts stored on your machine. A simple solution that goes a long way: ingest those transcripts and logs into a structured SQLite database, then search them with ranked text match. Everything is fully local and doesn't require anything fancy like a graph database or hosted memory service. This is the idea behind ctx, a Rust CLI that handles the ingestion and searching. We give our agents a skill that tells them to reference past sessions before working in an area. Usually we do this through an…
Jul 2026 · github.com
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Hi HN! Smooth CLI (https://www.smooth.sh) is a browser that agents like Claude Code can use to navigate the web reliably, quickly, and affordably. It lets agents specify tasks using natural language, hiding UI complexity, and allowing them to focus on higher-level intents to carry out complex web tasks. It can also use your IP address while running browsers in the cloud, which helps a lot with roadblocks like captchas (https://docs.smooth.sh/features/use-my-ip). Here’s a demo: https://www.youtube.com/watch?v=62jthcU705k Docs start at…
Feb 2026 · docs.smooth.sh
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At Laminar (https://github.com/lmnr-ai/lmnr) we're building open source AI observability platform in Rust. We obsess over instrumentation DX for our Python and TS SDKs and in this new blog we outline how we made the most seamless way of instrumenting recently released claude agent sdk
Dec 2025 · laminar.sh
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Hi HN! We just launched Codacy Guardrails, an IDE extension with a CLI for code analysis and MCP server that enforces security & quality rules on AI-generated code in real-time. It hooks into AI coding assistants (like VS Code Agent Mode, Cursor, Windsurf), silently scanning and fixing AI-suggested code that has vulnerabilities or violates your coding standards, while the code it’s being generated. We built this because coding agents can be a double-edged sword. They do boost productivity, but can easily introduce insecure or non-compliant code. One recent research team at NYU found that 40%…
2025
- 11TI
I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com
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Hey HN! I built Retain as the evolution of claude-reflect (github.com/BayramAnnakov/claude-reflect). The original problem: I use Claude Code/Codex daily for coding, plus claude.ai and ChatGPT occasionally. Every conversation contains decisions, corrections, and patterns I forget existed weeks later. I kept re-explaining the same preferences. claude-reflect was a CLI tool that extracted learnings from Claude Code sessions. Retain takes this further with a native macOS app that: - Aggregates conversations from Claude Code, claude.ai, ChatGPT, and Codex CLI - Instant full-text…
Jan 2026 · github.com
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Clink lets you use the coding agents you already pay for (Claude Code, Codex CLI, Gemini CLI, Z.ai GLM) to build → live-preview → ship apps in an isolated container. No token purchases, no extra cost for coding. Just link your existing Claude/OpenAI/Gemini account and start building and deploying instantly. Why we built this: Claude Code is our go-to for coding, but it lacked preview + deploy capabilities. We didn't want to pay Lovable again just for that. Different agents excel at different tasks - Claude Code for versatility, Codex for complex work, GLM for speed. We needed one…
Oct 2025 · clink.new
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Hi everyone! Hope you had a great day so far, and maybe its about to get just a little bit better (thanks Winter ;) So I had way to many terminal windows flying about when using Claude, and kept losing track of which terminal / session / project im in right now. So I built a solution for that, presented it to my team, and now we're using our new tool all the time, and developing it to be the most helpful agents organization tool we can think of. Unfortunatelly, Claude Code only for now, will do Codex soon tho. What it does for you: Main features: - Overview of your projects, with…
Aug 2026 · episko.dev
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Turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual understanding specific to your codebase. - trailhq/Graft
23d ago · github.com
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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We built HALO (Hierarchal Agent Loop Optimizer), an open-source tool for debugging and optimizing AI agents using their execution traces. It’s a loop. Run your agent, feed the traces to HALO, get the report, apply the fixes, then re-run your agent. HALO takes in OTEL compliant traces from AI agents using tracing frameworks such as Langfuse, Arize/OpenInference, or even just plain JSONL. It uses an RLM (Recursive Language Model) to more efficiently break trace analysis into smaller subproblems in order to find recurring patterns across large amounts of data and fix systemic issues that…
Jun 2026 · github.com
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Hello HN, Ever since agents have become increasingly common in development, I've been scratching my head as to how to control their randomness. Recently, I decided to emulate an issue-tracking and project-management tool for agent-driven workflows. Kanban is a Rust-based coordination layer designed to provide a feature-rich terminal interface and enforce rigorous workflows. It aims to be versatile and extendable, made to be tailored to any preferred flow. It comes with full git integration and guardrails such that only what truly benefits a project can go through. The workflow boils down to…
May 2026 · codeberg.org
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I built Hydra because I kept losing my flow when Claude Code hit usage limits mid-task. I would copy context, open another tool, and then re-explain everything. This would be super annoying for me. Hydra wraps your AI coding CLIs (Claude Code, Codex, OpenCode, Pi, or any terminal-based tool) in a single command. It monitors terminal output for rate limit patterns, and when one provider runs out, you switch to another with one keypress. Your conversation history, git diff, and recent commits are automatically copied to your clipboard so you can paste and keep going. The fallback chain is…
Apr 2026 · github.com
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Hey everyone! For the past two weeks my friend and I have been heads-down building Cloi, a fully local debugging agent that runs right in your terminal. You probably know the drill—every AI coding tool asks for API keys, subscriptions, and uploads your entire codebase to the cloud. Cloi does none of that: it runs entirely on your machine, with no cloud, no API keys, no subscriptions, and zero data leaving your system. What Cloi does: - Contextual error capture: Grabs your stack trace, local files, and environment to understand the issue. - Local LLM inference: Spins up Ollama on your box and…
2025 · github.com
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