How likely are we to look back on Agent/MCP/Skills as some early Netscape peculiarity? I would dive into adoption if I didn't think some new thing would beat the paradigm in a fortnight.
I've found the "too many tools polluting context" problem to be real. The challenge is that MCP servers often expose everything upfront, even when you only need a subset. The on-demand capability discovery pattern 'irrationalfab' mentioned makes sense having a lightweight index that the model can query, then pulling full tool details only when needed. This mirrors how we actually work with APIs we don't load all endpoints into memory, we discover them as needed.
I feel inspired and would like to donate my standard for Agent Personas to the community. A persona can be defined by a markdown file with the following frontmatter:
---
persona: hacker
description: logical, talks about computers a lot, enjoys coffee, somewhat snarky and arrogant
---
<more details here>
“inserted at the start of any query” feels like a bit of a misunderstanding to me. It plops the skill text into the context when it needs it or when you tell it to. It’s basically like pasting in text or telling it to read a file, except for the bit where it can decide on its own to do it. I’m not sure start, middle, or end of query is meaningful here.
The agentic development scene has slowly turned into a full-blown JavaScript circus—bright lights, loud chatter, and endless acts that all look suspiciously familiar. We keep wrapping the same old problems in shiny new packages, parading them around as if they’re groundbreaking innovations. How long before the crowd grows tired of yet another round of “RFC” performances?
Skills are a pretty awkward abstraction. They emerged to patch a real problem, generic models require fine-tuning via context, which quickly leads to bloated context files and context dilution (ie more hallucinations)
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
Interesting move. One thing I’m curious about is how opinionated the standard is supposed to be.
In practice, agent “skills” tend to blur the line between capabilities, tools, and workflows, especially once statefulness and retries enter the picture.
Is the goal here mostly interoperability between agent frameworks, or do you see this evolving into something closer to a contract for agent behavior over time?
I can imagine standardization helping a lot, but only if it stays flexible enough to avoid freezing today’s agent design assumptions.
I had developed a tool for Roo Code, and have moved over to anti-gravity with no problem, that basically gives playwright the ability to develop and test user scripts in an automated fashion.
It is functionally a skill. I suppose once anti-gravity supports skills, I will make it one officially.
Why does this need to be a standard in the first place. This isn't DDR5 lol, it's literally just politely asking the model to remember some short descriptions and read a corresponding file when it thinks appropriate. I feel like these abstractions are supposed to make Claude sound more sophisticated because WOW now we can give the guy new skills! But really they're just obfuscating the "data as code" aspect of LLMs which is their true power (and vulnerability ofc).
I have been switching between OpenCode and Claude - one thing I like about OpenCode is the ability to define custom agents. These can be ones tailored to specific workflows like PR reviews or writing change logs. I haven't yet attempted the equivalent of this with skills in Claude.
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?
I wish agentic skills were something other than a system prompt or a series of step-by-step instructions. feels like anthropicide and opportunity here to do something truly groundbreaking but ended up with prompt engineering.
All the talk about "open" standards from AI companies feels like VC-backed public LLM experiments. Even if these standards fade, they help researchers create and validate new tools. I see this especially with local models. The rise of CLI-based LLM coding tools lets me use models like GPT OSS 20B to build apps locally and offline.
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[ 0.23 ms ] story [ 59.7 ms ] threadAlthough 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
https://github.com/alganet/skills/blob/main/skills/left-padd...
Paper & applications published here: https://earthpilot.ai/metaskills/
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
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).