The AI worker glossary

An Agent Skill is markdown instructions an AI agent loads on demand to learn one technique. A worker kit is a configured worker that does a job unattended.

An agentic workflow is a process an AI agent carries out over several steps, deciding what to do next at each one rather than following a fixed script.

An AI plugin is an installable bundle adding skills, subagents and MCP config to an AI client you drive. An AI worker runs one job unattended, on its own key.

An AI worker is an AI agent configured for a defined job, with its own app permissions, spending limits, memory and run record retained between requests.

AI worker fleet orchestration is one AI client splitting a task across purpose-built workers, then reading their results back to decide what happens next.

An AI workforce is the set of AI workers a company runs, with each job's method, permissions, limits and run record retained between requests.

An app firewall decides which connected apps an AI worker may reach and at what level, so it holds only the access you granted, never your whole account.

BYOK, bring your own key, is adding your own model provider API key so token usage bills straight to your provider account instead of the platform's balance.

Calibrated confidence is a model score that matches reality: of the answers it rates 0.8, about 80 percent turn out right, so the number can be acted on.

A confidence threshold is the score an automated decision must clear before it is acted on, sending anything below it to a person instead.

A connected app is an account you have signed in to WorkerKit once, which workers can then be granted access to per app and per level.

Contact rules decide which people an AI worker may read about or contact, applied above app permissions so inbox access does not mean reaching everyone in it.

A kit publisher is whoever authored and published a worker kit to the directory, and whose page carries every kit they maintain.

A managed runtime is the platform that operates an AI worker for you: it holds app access, runs it on schedule, enforces limits and records what happened.

MCP, the Model Context Protocol, is an open standard that lets an AI agent reach external tools and data through one common interface.

Model agnostic means the same AI worker runs on any supported model, so you pick at deploy time and can switch later without rewriting the worker.

A per-model grade scores how well one kit performs on one AI model, marked with whether it was measured from real runs or declared by the publisher.

An open app slot is a kit naming the app surface a job needs, such as email, and letting you choose which provider fills it when you install.

A private kit is a worker kit kept out of the public directory, available to you or your team rather than published for anyone to install.

Redaction strips or masks sensitive values out of what an AI worker sends to a model or writes into an app, so the information never leaves at all.

A run receipt is the record an AI worker leaves after every run showing what it read, what it did, what it cost and what it skipped.

A runtime wallet is a prepaid balance that hosted AI worker runs draw on to pay for model tokens, kept separate from the subscription price.

Structured output is a model answer constrained to a schema the caller declared, so the result parses reliably instead of being read out of prose.

A System One model is an AI model that answers typed questions about data you supply with a pick, a score or a probability, never generated text.

A tool call is one action an AI worker takes in a connected app, such as reading a thread or adding a calendar event, and it is the unit plans meter.

A webhook trigger is an inbound HTTP call that starts an AI worker the moment something happens in another system, instead of waiting for its next run.

A worker fleet is the set of AI workers running in one account, each doing one narrow job with its own key and its own app permissions.

A worker kit is a ready-made AI worker packaging instructions or decision rules, app permissions, and setup for one job, ready to run with your own accounts.

Worker memory is the facts and rules an AI worker carries between runs, so it does not start every run knowing nothing about your business.

A worker schedule is a standing instruction that runs an AI worker on a cadence in your own time zone, without anyone asking it to.

The WorkerKit CLI is the open-source wk command-line tool for managing and running an account's AI workers and browsing the kit directory from the terminal.

The WorkerKit MCP server at mcp.workerkit.ai is a remote endpoint that lets any MCP client manage and run an account's AI workers, and search the kit directory.