Although Skills are just md files but it’s good to see them “donate” it.
There goal seems to be simple: Focus on coding and improving it. They’ve found a great niche and hopefully revenue generating business there.
OpenAI on the other hand doesn’t give me same vibes, they don’t seem very oriented. They’re playing catchup with both Google models and Anthropic
Apple has shortcuts, but they haven’t propped it up like a standard that other people can use.
To contrast this is something you can use even if you have nothing to do with Claude, and your tools created will be compatible with the wider ecosystem.
Many many MCPs could and should just be a skill instead.
Might add this to the next https://hackernewsai.com/ newsletter.
I'm authoring equivalent in CUE, and assimilating "standard" provider ones into CUE on the fly so my agent can work with all the shenanigans out there.
We'll see how many of these are around in a few years.
MCP lets you glue random assed parts of services to mega-ultra-high critical business initiatives with no go between. Delivered through a personalized chat interface that will tell you how sexy you are and how you deserved to win at golf yesterday… from salesman to auto interface to forever contract in minutes.
MS sells to insecurities of incompetent management and facilitates territory marking at the expense of governments and societies around the world for mega bucks. MCP, obvious as it is technically, also lets them plug a library into existing services for a quick upgrade then an atomized upsell directly to the chat interfaces of upper management.
Microsoft’s CEO has talked about his agent swarm. Much like RPA this woo appeals strongly to the barely technical.
The reason I ask is that the pace of new things arriving is overwhelming, hence I was tempted to just ignore it. Not because things had signs of transience, but because I was drowning and didn't know where to start. That is not the same thing as actually observing signs of things being too foamy.
Right now models have roughly all of the written knowledge available to mankind, minus some obscure held out private archives and so on. They have excellent skills and general abilities to construct plausible sequences of actions to accomplish work, but we need to hold their hands to really get decent performance across a wide range of activities. Skills and agent frameworks and MCP carve out different domains of that problem, with successful solutions providing training data for future models that might be able to be either generalized, or they'll be able to create a vast mountain of synthetic data following successful patterns, and make the next generation of models incredibly useful for a huge number of tasks, by default.
It might also be possible that by studying the problem, identifying where mode collapses and issues with training prevent the right sort of generalization, they might tweak the architecture and be able to solve the deficiency through normal training runs, and thereby discard the need for all the bespoke artisanal agent specifications.
However the "waiting out" strategy needs a timeout. It might happen that agentic crutches around LLMs will bear fruit much sooner than high-quality LLMs arrive. If you don't have a timeout or a decent exit criteria you may end up waiting indefinitely, or at least until reality of things becomes too painful to ignore.
The "ski rental problem" comes to mind here, but maybe there is another "wait it out" exit strategy?
Sorry for the nit, but this is a gross oversimplification. Most private archives are not obscure but obfuscated and largely are way more valuable training data then the publicly available ones.
Want to know how the DOD may technically tracks your phone? Private.
Want to know how to make Coca Cola at scale? Private.
Want to know what the schematic is for a Google TPU? Private.
etc etc.
You can have the most capable human available to you, a supreme executive assistant. You still have to convey your intent and needs to them, your preferences, etc, with as high a degree of specificity as necessary.
And you need to provide them with access and mechanisms to do things on your behalf.
Agentic definitions are the former, and they will evolve and grow. I like the metaphor of deal terms in financial contracts- benchmarkers document billions of these now. The "deal terms" governing the work any given entity does for you will be rich and bespoke and specific, like any valuable relationship. Even if the agent is learning about you, your governance is still needed.
MCP is the latter. It is the protocol by which a thing does things for you. It will get extensions. Skill-like directives and instructions will get delivered over it.
Skills themselves are near term scaffold that will soon disappear.
The problem isn’t having a standard way for agents to branch out. The problem is that AI is the new Javascript web framework: there’s nothing wrong with frameworks, but when everyone and their son are writing a new framework and half those frameworks barely work, you end up with a buggy, fragmented ecosystem.
I get why this happens. Startups want VC money, established companies then want to appear relevant, and then software engineers and students feel pressured to prove they’re hireable. And you end up with one giant pissing contest where half the players likely see the ridiculousness of the situation but have little choice other than to join party.
MCP does three things conceptually: it lets you build a bridge between an agent and <something else>, it specifies a UI+API layer between the bridge and the LLM, and it formalizes the description of that bridge in a tool-calling format.
It's that UI+API layer that's the biggest pain in the ass, in my opinion. Sometimes you need it; for instance, if you wanted an agent to access your emails, a high quality MCP server that can't destroy your life through enthusiastic tool calling makes sense.
If, however, you have, say a CLI tool or simple API that's reasonably self documenting and you're willing to have it run, and/or if you need specific behavior with a different context setting, then a skill can just be a markdown file that explains what, how, why.
The agent loop architectural pattern (and that’s the relevant bit) is going to continue to matter. There will be new patterns for sure, but tool calling plus while loop (which is all an “agent” is) is powerful and highly general.
https://github.com/alganet/skills/blob/main/skills/left-padd...
Either way, that’s hilarious. Well done.
<conspiracy_mode> maybe all of them were designed to occupy the full context window of earlier GPT models </conspiracy_mode>
It's a much better system in my experience.
What they said was don't pollute your context with lots of tool defs, from MCP or not. You'll see this same problem if you have 100s of skills, with their names and descriptions chewing up tokens
Their solution is to let the agent search and discover as needed, it's a general concept around tools (mcp, func, code use, skills)
There's no real benefit to the MCP protocol over a regular API with a published "client" a local LLM can invoke. The only downside is you'd have to pull this client prior.
I am using local "skill" as reference to an executable function, not specifically Claude Skills.
If the LLM/Agent executes tools via code in a sandbox (which is what things are moving towards), all LLM tools can be simply defined as regular functions that have the flexibility to do anything.
I seriously doubt MCP will exist in any form a few years from now
Paper & applications published here: https://earthpilot.ai/metaskills/
---
persona: hacker
description: logical, talks about computers a lot, enjoys coffee, somewhat snarky and arrogant
---
<more details here>"you're absolutely right!"
Please tell us how REALLY feel about JavaScript.
1. For an experienced Claude Code user, you can already build such an agent persona quite trivially by using the /agents settings.
2. It doesn't actually replace agents. Most people I know use pre-defined agents for some tasks, but they still want the ability to create ad-hoc agents for specific needs. Your standard, by requiring them to write markdown files does not solve this ad-hoc issue.
3. It does not seem very "viral" or income-generating. I know this is premature at this point, but without charging users for the standard, is it reasonable to expect to make money off of this?
Inversely, you can persist/summarize a larger bit of context into a skill, so a new agent session can easily pull it in.
So yes, it's just turtles, sorry, prompts all the way down.
This may all be very wrong, though, as it's mostly conjecture from the little I've worked with skills.
BUT what makes them powerful is that you can include code with the skill package.
Like I have a skill that uses a Go program to traverse the AST of a Go project to find different issues in it.
You COULD just prompt it but then the LLM would have to dig around using find and grep. Now it runs a single executable which outputs an LLM optimised clump of text for processing.
Apart from Google Inc., I have not seen a single "AI company" propose an RFC that was reviewed by the IETF and became a proper internet standard. [0]
"MCP" was one of the worst so-called "standards" ever built since the JWT was proposed. So I do not take Anthropic seriously when they create so-called "open standards" especially when the reference implementation is in Javascript or TypeScript.
> I have not seen a single "AI company" propose an RFC that was reviewed by the IETF and became a proper internet standard.
Why would the IETF have anything to do with LLM/agent standards? This seems like a category error. They also don’t ratify web standards, for example.
IETF is involved in protocol standards, MCP/A2A are certainly in this category, skills less so
like deno vs npm package ecosystems that didn't work together for many years
There are multiple AGENTS vs CLAUDE vs .github/instructions; skills vs commands; ... intermixed and inconsistent concepts, all out in the wild
When I work on a project, do all the files align? If I work in an org, where developers have agent choice, how many of these instructions and skills "distros" do I need to put (pollute?) my repo with?
While I do agentic development in personal projects a lot at this point, at work it's super rare beyond quick lookups to things I should already know but can't be arsed to remember exactly (like writing a one-off SQL scripts which does batching mutations and similar)
But skills dont really solve the problem. Turning that workaround into a standard feels strange. Standardizing a patch isn’t something I’d expect from Anthropic, it’s unclear what is their endgame here
I think that they often do solve the problem, just maybe they have some other side effects/trade offs.
The best one we have thought of so far.
Marketing. That defines pretty much everything Anthropic does beyond frontier model training. They're the same people producing sensationalized research headlines about LLMs trying to blackmail folks in order to prevent being deleted.
The value of standardizing skills is that the skills you define work with any agentic tool. Doesn't matter how simple they are, if they dont work easily, they have no use.
You need a practical and efficient way to give the llm your context. Just like every organization has its own standards, best practices, architectures that should be documented, as new developers do not know this upfront, LLMs also need your context.
An llm is not an all knowing brain, but it’s a plan-do-check-act text processing machine.
This is not the first time, perhaps expectation adjustment is in order. This is also the same company that has an exec telling people in his Discord (15m of fame recently) Claude has emotions
It has been published as an open specification.
Whether it is a standard isn't for them to declare.
It is functionally a skill. I suppose once anti-gravity supports skills, I will make it one officially.
These two solutions look feel and smell like the same thing. Are they the same thing?
Any OpenCode users out there have any hot or nuanced takes?
And of course Claude Code has custom slash commands which are also very similar.
Getting a lot of whiplash from all these specifications that are hastily put together and then quickly forgotten.
It does code execution in an apple container if your Skill requires any code execution.
It also proves the point that Skills are basically repackaged MCPs (if you look into my code).
For example, you can't have a directory named "Stripe-Skills" which will give you a breakdown of last week's revenue (unless you write in the skills how to connect to stripe and get that information). So, most of the remote, existing services are better used as MCPs (essentially APIs).
Could one make a copyleft type license such that the generated code must be licensed free and open and under the same license? How enforceable are licenses on these skills anyway, if one can take in the whole skill with an agent and generate a legally distinct but functionally close variant?
albingroen•3h ago