Moves

Without recommended next actions, the world model is informative but not action-guiding. Moves turn understanding into direction: the engine's ranked answer to "given what the agent currently believes, what should it investigate next?" Each move targets a specific belief, gap, or contradiction and reports how much acting on it would sharpen the agent's picture.

What a Move Is

A move is a recommended action the system surfaces based on the current belief state. Each move has an action type, a target, a reason, and an expected value representing how much it would improve the agent's understanding.

1{
2  action: 'gather_evidence',
3  target: 'Missing APAC market analysis',
4  reason: 'High-impact gap with 3 downstream dependencies',
5  value: 0.72,
6  executor: 'agent',
7}

• action. The type of move: clarify, resolve_uncertainty, gather_evidence, compare_paths.
• target. The belief, gap, or contradiction the move addresses.
• reason. Why this move matters, in natural language.
• value. How much this move would reduce uncertainty, 0–1. Higher means a bigger shift in the picture.
• executor. Who should act: agent, user, or both.

Move Types

Each action can have a subtype for specificity:

How Moves Are Ranked

Moves are ranked by how much they would reduce uncertainty in the beliefs that matter most.

A gap with many downstream dependencies generates a higher-value move than a gap with none. A contradiction between two load-bearing beliefs (beliefs that other beliefs derive from, so if they're wrong the rest collapse) generates a higher-value clarify move than a contradiction between peripheral claims that nothing depends on.

The system considers:

• How much uncertainty the move would reduce
• How many other beliefs depend on the target
• Whether the target belief is load-bearing (see Clarity for how the engine identifies them)
• The current clarity score and what would improve it most

Reading Moves

Moves are returned from every major SDK method:

1// Before the agent acts
2const context = await beliefs.before(userMessage)
3console.log(context.moves)  // ranked actions for this turn
4
5// After the agent acts
6const delta = await beliefs.after(result.text)
7console.log(delta.moves)    // updated recommendations
8
9// Full world state
10const world = await beliefs.read()
11console.log(world.moves)    // all current recommendations

Routing on Moves

Use moves to direct agent behavior:

1const delta = await beliefs.after(result.text)
2const next = delta.moves[0]
3
4if (!next) {
5  // No recommended actions. Clarity is likely high.
6  await finalize(delta.state)
7} else if (next.action === 'gather_evidence') {
8  await runResearch(next.target)
9} else if (next.action === 'clarify') {
10  await resolveContradiction(next.target)
11} else if (next.action === 'resolve_uncertainty') {
12  await deepDive(next.target)
13} else if (next.action === 'compare_paths') {
14  await presentTradeoffs(next.target)
15}

Executor

The executor field indicates who should act on the move.

A user executor move might surface when the system detects a value judgment or strategic decision that the agent should not make alone.