What is action space?
The set of actions an agent is allowed to choose from at a given step.
01 · Foundations · 103 terms
Foundations covers the basic objects and behaviors that make an agent an agent. This section has 103 definitions. Open any term for a plain answer, the source behind it, and the day we checked it. Related links take you to the ideas that explain it or show where it sits in the wider field.
The set of actions an agent is allowed to choose from at a given step.
A search method where the system chooses what to find, checks it, and may search again before it answers.
The power to choose goal-led actions within a given setting.
A file that tells other systems who an agent is, what it can do, and how to reach it.
The process by which a user or another system finds an agent and learns what it can do.
The repeated cycle in which an agent observes, decides, acts, checks the result, and chooses what to do next.
A file that lists an agent’s purpose, tools, limits, inputs, outputs, and rules.
Ways for agents to ask for, approve, send, or receive money within set limits.
A list of agents, what they can do, and where other systems can reach them.
A reusable set of instructions and tools that gives an agent a named ability.
Two or more agents with assigned roles that cooperate on one goal.
Able to seek results on its own, especially when used of AI.
AI designed to choose and carry out actions toward a goal, often through one or more agents.
Trade in which agents help find, buy, sell, or pay for goods under set rules.
RAG in which an agent plans and changes its searches to meet a goal.
A system that observes a setting, chooses goal-led actions, and acts on that setting.
A point where an agent must stop and get consent before it takes a high-risk step.
A machine system that predicts or makes choices for goals set by people.
Tool use in which the agent chooses when, why, and how to call a tool without approval for each call.
A check that the system initiates and runs on its own before accepting or advancing work.
The degree to which an agent can choose and carry out actions without new human direction.
An agent that works without an open user session. A clock or event may start it.
A design in which several agents or modules read from and write to one shared working state.
The process of finding what tools, skills, services, or agents are available for a task.
Text or tokens a model produces as steps before an answer. They may not show its true internal reasoning.
A control that stops an agent after a risk alert, repeat failure, cost limit, or unsafe state.
The practice of tying a factual statement to evidence that can be checked.
A mistake that changes later choices, causing the size or cost of the error to grow across a run.
A failure where someone tricks a trusted system into misusing its access.
Work that can survive a restart, wait for an event, and resume from saved state.
A system that selects or changes the model it uses according to the task, state, cost, or risk.
A real or simulated world where an agent acts through a body, robot, or set of sensors.
The exchange in which an agent observes a world, acts on it, and receives new information in return.
Finding a failure, returning to a safe state, and choosing the next useful step.
Sending a choice or problem to a person or system with more power or skill.
An agent that starts or changes work when a declared event occurs.
A risk in which an agent has more functions, permissions, or freedom than its task needs.
A way to improve later choices by using signals from past results.
The maximum age evidence may reach before it must be checked again.
A model feature that names a function and gives the inputs for software to run it.
The range of tasks and settings in which a system can work without being rebuilt for each one.
How well a system keeps its choices aimed at a stated result.
A method that maps ideas as a graph so they can branch, link, and change.
Search guided by an estimate of which options are most likely to lead to a good result.
A design in which a person must take part in selected decisions or stages of the work.
A design in which an agent acts on its own while a person monitors and can intervene.
A property that lets the same action run again without causing a second change.
An attack where bad instructions hide in data an agent reads, such as a page, file, email, or tool result.
A signal that pauses or stops an agent so its state can be inspected, changed, or resumed.
A model used to score or compare another model’s output or behavior.
An AI model trained on vast amounts of text to understand and generate language.
The rule that a user, agent, or service should receive only the access needed for its current task.
The use of a language model to grade, rank, or critique outputs under a stated rubric.
An agent role shaped mainly by instructions about its skills, duties, and limits.
An agent designed to continue across long waits, many steps, or more than one user session.
A name used by the community around OpenClaw.
A plan search that samples possible outcomes and spends more effort on promising paths.
A setting where an agent mainly sees and acts through written or spoken words.
The chance that at least one of k attempted outputs passes a test.
Tool use in which software or a fixed workflow decides when the tool runs rather than the model deciding.
A check that observes or scores work without controlling what happens next.
A cycle where an agent sees its setting, takes an action, and checks the result.
An agent pattern that first creates a plan and then carries out its steps, revising when needed.
An attack that puts commands in model input to override the task or rules.
A claim shown with a warning because its evidence is not yet strong enough.
Tool use that finds outside facts and puts them into the model’s context.
An agent pattern that puts thought, action, and observation steps in a loop.
The deliberate search for ways a system can fail, be misused, or be attacked.
A step in which an agent reviews earlier work and uses the review to change what it does next.
An agent set up for a clear job, duty, or field of work.
An agent that decides which specialist, model, tool, or workflow should receive a request.
A setting whose state or replies change through explicit rules.
A closed setting that limits what code or an agent can reach and change.
A graph of possible states or ideas, linked by available moves or known ties.
The order and method used to visit options in a search tree or graph.
A branching map of choices and the states that may follow them.
Stealing passwords, keys, private data, or other guarded facts from a system.
A model’s review of its own work against clear rules.
A loop where a model reviews and rewrites its own output.
An account that lets software or a workload prove its identity and gain access.
Information that more than one agent or component can read or change during a task.
A list of reusable skills, what they do, how to call them, and what they need.
A record of where information came from and how it was collected or changed.
An agent that assigns work, watches other agents, and chooses when to retry, raise an issue, or stop.
The world, tools, rules, and feedback within which an agent attempts a task.
A defined measure of whether an agent achieved the intended outcome.
A rule that tells an agent loop when to stop.
The process by which a model or agent requests that software run a named tool with stated arguments.
Finding tools and learning their names, inputs, outputs, and limits.
A failure returned when a tool cannot finish a request as asked.
One specific request to run a tool with a set of arguments.
An attack that alters a tool, its description, or its output so an agent is misled or compromised.
A directory that lists tools and the information needed to discover and call them.
The data or error returned after a tool invocation.
A structured description of a tool’s name, purpose, inputs, and output shape.
The decision about which available tool, if any, should be used for the current step.
The use of an outside tool for its result or for the change it causes.
The ordered record of an agent’s states, actions, inputs, and outputs during a run.
A method that explores several branches of thought and compares their value.
Work that leaves enough evidence for another party to check what ran and which rules it followed.
The rules and expected behavior that govern how an agent browses, collects, and acts on the web.
An agent that does tasks assigned by a lead agent or system.
A map an agent uses to predict how its world may change after an action.