This video introduces "Agent Skills," an open standard for AI agent capabilities developed by Anthropic and adopted by 37 tools. The core concept of a skill is a single folder containing a `skill.md` file. This file includes essential fields like `name` and `description`, along with instructions for the agent. The system also supports additional components: a `scripts` folder for executable code, a `references` folder for on-demand documentation, and an `assets` folder for templates.

The key innovation highlighted is "progressive disclosure." This approach ensures efficiency by loading skills in stages:

1.  **Discovery:** At startup, only the skill's name and description (approx. 100 tokens) are loaded.
2.  **Activation:** When a user's task matches a skill's description, the full `skill.md` content is loaded into the agent's context.
3.  **Execution:** Scripts and reference files are loaded only when required for the task.

This staged loading keeps skills small until they are actively needed. The `skill.md` file itself is described as a simple markdown file, without requiring a specific Domain-Specific Language (DSL) or Software Development Kit (SDK), and can be stored directly in a Git repository. It includes required fields (name, description) and optional fields (license, compatibility, metadata, pre-approved tools), followed by markdown instructions.

The token economy is also explained: 100 tokens to advertise a skill, 5,000 tokens to run it, and zero tokens until activation. This efficient model allows for many skills with a small context footprint.

Agent Skills are compatible with numerous platforms, including Plot, Cursor, VS Code, and OpenAI Codex, requiring no rewrites due to the standardized format. The format originated from Anthropic and was released as an open standard, encouraging community contributions.

The video concludes by posing a question to the audience about whether "Skills" or "MCP" (presumably another standard or technology) should be prioritized, directing viewers to agentskills.io for the full specification.

DIY Smart Code

Agent skills, the open standard for AI agent capabilities built by Enthropic, adopted by 37 tools. Here is how it works in under three minutes.

A skill is one folder. Inside lives one file: skill.md. That file holds two fields: a name, a description, plus the instructions an agent follows to do the work. That is the whole spec.

A skill is more than just skill.md, though. Drop scripts into a scripts folder and the agent runs them. Drop reference docs into a references folder and the agent reads them on demand. Drop templates into assets and the agent uses them.

Here is the part that makes it actually work: progressive disclosure. Stage one, discovery. At startup, the agent loads only each skill's name and description. About 100 tokens each.

Stage two, activation. When your task matches the description, the full skill.md loads into context.

Stage three, execution. Bundle scripts and reference files only load when the work demands them. Skills stay small until you need them.

This is what a real skill.md looks like. Required fields: a name, a description. Optional fields: a license, compatibility hints, metadata, even pre-approved tools, then markdown instructions. No DSL, no SDK, just a file in your Git repo.

Here is the receipt: 100 tokens to advertise a skill, 5,000 tokens to run it. Zero tokens until activation. Many skills, tiny context footprint.

So where can you use it? Plot code, Cursor, VS Code, OpenAI Codex, and dozens more. Same file, same format, zero rewrites.

The format was originally developed by Entropic, then released as an open standard, open to contributions from anyone in the ecosystem.

So, one question: skills or MCP, which one earns the spot in your stack first? Drop your pick in the comments.

Full spec at agentskills.io.

The Anthropic Standard Revolutionizing AI Agents #ai #shorts

Agent skills, the open standard for AI
agent capabilities
built by Enthropic adopted by 37 tools.
Here is how it works in under three
minutes. A skill is one folder inside
lives one file. skill.md that file holds
two fields. A name, a description, plus
the instructions an agent follows to do
the work. That is the whole spec. A
skill is more than just skill.md though.
Drop scripts into a scripts folder and
the agent runs them. Drop reference docs
into a references folder and the agent
reads them on demand. Drop templates
into assets and the agent uses them.
Here is the part that makes it actually
work. Progressive disclosure. Stage one,
discovery. At startup, the agent loads
only each skills name and description.
About 100 tokens each. Stage two,
activation.
When your task matches the description,
the full skill.m MD loads into context.
Stage three, execution. Bundle scripts
and reference files only load when the
work demands them. Skills stay small
until you need them. This is what a real
skill.md looks like. Required fields, a
name, a description, optional fields, a
license, compatibility hints, metadata,
even pre-approved tools, then markdown
instructions.
No DSL, no SDK, just a file in your Git
repo. Here is the receipt. 100 tokens to
advertise a skill. 5,000 tokens to run
it. Zero tokens until activation.
Many skills, tiny context footprint. So
where can you use it? Plot code, cursor,
VS code, open AI codeex, and dozens
more. Same file, same format, zero
rewrites. The format was originally
developed by Entropic,
then released as an open standard, open
to contributions from anyone in the
ecosystem. So, one question, skills or
MCP, which one earns the spot in your
stack first? Drop your pick in the
comments. Fullsp spec at agentskills.io.

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The Anthropic Standard Revolutionizing AI Agents #ai #shorts

Transcription