Terms that show up across the skills catalog, the agents pages, and our posts, defined once so other pages can link here instead of repeating them.
Skills
A skill is a written procedure an AI can follow. It’s a folder with instructions, examples, and sometimes scripts. It captures how a specific job gets done: the steps, the judgment calls, the format of the output. A skill doesn’t run on its own. Something has to invoke it.
Agents
An agent is the thing that runs. It has a model, a set of tools, and a loop: read the situation, decide, act, check, repeat. Agents pick up skills and use them. One agent can run many skills. A skill is the recipe, the agent is the cook.
Tokens
Tokens are the smallest individual units a language model works with, and can correspond to words, subwords, characters, or bytes. For Claude, a token is roughly 3.5 English characters, though the exact count varies by language. Tokens are usually invisible when you’re just chatting with a model, but they’re what you’re actually paying for, and what shows up on the bill once a workflow runs at volume.
Context Window
The context window is how much text a model can look back on and reference while generating new text. Think of it as the model’s working memory, not the much larger set of data it was trained on. A larger context window handles longer, more complex prompts; a smaller one limits how much the model can hold onto across a long task or conversation.
LLM
A large language model (LLM) is trained on a large amount of text and can generate human-like text, answer questions, summarize information, and carry out a wide range of language tasks. Claude, the AI assistant built by Anthropic, is a large language model that’s been further trained and fine-tuned using RLHF.
Prompt Caching
Prompt caching lets a model resume from a specific prefix it’s already processed instead of reprocessing it from scratch. For any task that repeats the same instructions or reference material across multiple calls, this cuts both processing time and cost.
Classification
Classification is sorting an input into a category from a known list. Is this email a lead, a vendor invoice, or noise? Is this transaction COGS or opex? The possible answers exist before you start; the work is deciding which one applies. In a business brain, classification is what turns a pile of files into a queryable structure, by putting every item into a type the system already understands.
Extraction
Extraction is pulling specific facts out of unstructured material and putting them into fields: reading a contract and returning the counterparty, term length, renewal date, and payment terms; reading a call transcript and returning who committed to what. Classification asks “which bucket.” Extraction asks “what are the values.” Extraction is how a business brain gets built in the first place, by turning documents, calls, and what’s in people’s heads into structured records.
Formatting
Formatting is shaping output so it lands where it needs to go, in the form that place expects: the same content as a markdown note for a vault, JSON for an API, HTML for a CMS, or a table for a brief. Formatting carries no judgment about what’s true, only how it’s presented. It’s the cheapest layer to automate, and the one people most often confuse with the actual thinking.