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Hacker News Show HN: Ctx, save tokens by loading only the relevant tools

Positioned to 'save tokens by loading only the relevant tools' and 'avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all.' It is presented as complementary to other token reduction tools, aiming to 'save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses.'

5
Traction Score
0
Discussions
Jun 17, 2026
Launch Date
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Product Positioning & Context

AI Executive Synthesis
Positioned to 'save tokens by loading only the relevant tools' and 'avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all.' It is presented as complementary to other token reduction tools, aiming to 'save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses.'
Ctx addresses a critical and escalating pain point in LLM application development: token cost and context window management. Its 'upstream' approach to pre-filtering relevant tools and context represents a significant architectural optimization, directly impacting operational efficiency and cost-effectiveness for businesses deploying LLM-powered agents. The reliance on a curated graph of tooling ensures repeatability and mitigates hallucination risks, crucial for enterprise adoption where reliability is paramount. This product highlights the emerging need for intelligent orchestration layers that manage the complexity and resource consumption of sophisticated AI systems, enabling developers to scale LLM applications more economically and reliably by preventing context bloat before it occurs.
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
Token cost in-line token reduction compress requests / responses routers that pick the right model narrow down the amount of available tools, skills and mcps based on repo/context accumulate skills, agents, MCP servers, harnesses, prompts, repo instructions, local scripts context before the session gets bloated watching the repo and task

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Deep-Dive FAQs

What is Ctx, save tokens by loading only the relevant tools?
Ctx, save tokens by loading only the relevant tools is analyzed by our AI as: Positioned to 'save tokens by loading only the relevant tools' and 'avoid loading irrelevant skills, agents, MCPs, and harnesses into context at all.' It is presented as complementary to other token reduction tools, aiming to 'save tokens without forcing the user to manually test and compare thousands of possible skills, agents, MCP servers, and harnesses.'. It focuses on Ctx addresses a critical and escalating pain point in LLM application development: token cost and context window management. Its 'upstream' approac...
Where did Ctx, save tokens by loading only the relevant tools originate?
Data for Ctx, save tokens by loading only the relevant tools was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Ctx, save tokens by loading only the relevant tools publicly launched?
The initial public indexing or launch date for Ctx, save tokens by loading only the relevant tools within our tracked developer communities was recorded on June 17, 2026.
How popular is Ctx, save tokens by loading only the relevant tools?
Ctx, save tokens by loading only the relevant tools has achieved measurable traction, logging over 5 traction score and facilitating 0 recorded discussions or engagements.
Which technical categories define Ctx, save tokens by loading only the relevant tools?
Based on metadata extraction, Ctx, save tokens by loading only the relevant tools is categorized under topics such as: Token cost, in-line token reduction, compress requests / responses, routers that pick the right model.
What are some commercial alternatives to Ctx, save tokens by loading only the relevant tools?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as PI-Link Speed Radar, which offers overlapping value propositions.
How does the creator describe Ctx, save tokens by loading only the relevant tools?
The original author or development team describes the product as follows: "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 usuall..."

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