惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

腾讯CDC
The Cloudflare Blog
IT之家
IT之家
V
V2EX
雷峰网
雷峰网
MyScale Blog
MyScale Blog
P
Proofpoint News Feed
Stack Overflow Blog
Stack Overflow Blog
博客园 - Franky
Engineering at Meta
Engineering at Meta
S
SegmentFault 最新的问题
GbyAI
GbyAI
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 司徒正美
云风的 BLOG
云风的 BLOG
小众软件
小众软件
博客园 - 叶小钗
Blog — PlanetScale
Blog — PlanetScale
C
Check Point Blog
A
About on SuperTechFans
B
Blog
月光博客
月光博客
宝玉的分享
宝玉的分享
Last Week in AI
Last Week in AI

HN's home page

Rainbow Query Language | Hacker News Exec into Node via Kubectl An AI native hedge fund The Seven-Action Documentation Model | Hacker News Package Manager for Kubectl Plugins Tongan Castaways | Hacker News Tech overlords plan for conscious AI to conquer the cosmos. What could go wrong? Data Breach Disclosure Lag Is Getting Worse How LLMs Work | Hacker News I Dropped PRDs for Shape Up Go Experiments Explained | Hacker News FCA's Palantir deal could expose UK financial data to Trump's US, critics fear WebXR BCI for Neural-Adaptive Avatar Control in Mixed Reality The first murder conviction via DNA analysis Tom Interviews Theo de Raadt of the OpenBSD Project (2019) [video] Show HN: Replace shell commands with bun shell typescript scripts Quay.io Is Down | Hacker News AI driven analysis of brokerage account fees in the UK Bill Gates Spent Years Crafting His Image. Now It's Cracking Using LLMs to secure source code Wi-Fi 8 in the Lab [video] The household battery revolution that could change energy bills and the world Is Python Becoming Pinyin? | Hacker News Livia – Executive Assistant | Hacker News FindMyPipe – Query Apple Find My from Linux for AI Agents Show HN: Agent skill for creating product launch videos with Remotion RecruitMyself – AI job search copilot for resumes and applications AI coding agents and the erosion of system understanding The 'Resting' Generation and South Korea's Youth Recession AMD Computex 2026: 10 Years of AM4, AM5 Support Through 2029
Show HN: Ctx, save tokens by loading only the relevant tools
stevesolun · 2026-06-17 · via HN's home page

Hi HN!

Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests / responses as much as possible.

But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo/context?

People usually accumulate skills, agents, MCP servers, harnesses, prompts, repo instructions, and local scripts. I’m not saying we are all hoarders, but we sort of are. When did you remove a skill recently? After a while, the model has way too many options to choose from.

ctx tries to fix that by selecting context before the session gets bloated.So no, it doesn’t cleanup your messy garage, but it gives you magic glasses that let you focus only on the tools you need.

It does it by watching the repo and task, walks a graph of available tooling, and recommends a small top-scored bundle of skills, agents, MCP servers, and harnesses.

How does it know? To make sure results are not hallucinated, and repeatable, I curated a list of 91k+ skills, 467 agents, 10.7k MCP servers, 207 harnesses, and built a graph to help ctx make decisions on what to recommend. While I used AI to generate it of course, I curated it and revised it to make sure the data is up to date.

So how this is different from rtk, caveman, ponytail, and similar token-saving tools?

As mentioned above those tools mostly reduce tokens after something is already being used.

rtk compresses command output.

caveman-style tools make the assistant respond with fewer words.

ponytail, is, well, awesome, but again it focuses more on reducing code (YAGNI)

ctx is upstream. It tries to avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all.

So it is not really a replacement. It should work side by side with them!

Use ctx to choose the right tools. Use rtk to reduce terminal-output noise. Use terse-output tools if you want shorter responses.

The goal is simple: save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses.

Repo: https://github.com/stevesolun/ctx