Stop Conditions

Basic Usage

import { OpenRouter, stepCountIs } from '@openrouter/agent';

const openrouter = new OpenRouter({
  apiKey: process.env.OPENROUTER_API_KEY,
});

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Research this topic thoroughly',
  tools: [searchTool, analysisTool],
  stopWhen: stepCountIs(5), // Stop after 5 steps
});

Built-in Stop Conditions

stepCountIs(n)

Stop after a specific number of steps:

import { stepCountIs } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Analyze this data',
  tools: [analysisTool],
  stopWhen: stepCountIs(10), // Stop after 10 steps
});

hasToolCall(name)

Stop when a specific tool is called:

import { hasToolCall } from '@openrouter/agent';

const finishTool = tool({
  name: 'finish',
  description: 'Call this when the task is complete',
  inputSchema: z.object({
    summary: z.string(),
  }),
  execute: async (params) => ({ done: true }),
});

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Research until you have enough information, then call finish',
  tools: [searchTool, finishTool],
  stopWhen: hasToolCall('finish'), // Stop when finish tool is called
});

maxTokensUsed(n)

Stop after using a certain number of tokens:

import { maxTokensUsed } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Generate content',
  tools: [writingTool],
  stopWhen: maxTokensUsed(5000), // Stop after 5000 total tokens
});

maxCost(amount)

Stop after reaching a cost threshold:

import { maxCost } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5.2',
  input: 'Perform extensive analysis',
  tools: [analysisTool],
  stopWhen: maxCost(1.00), // Stop after $1.00 spent
});

finishReasonIs(reason)

Stop on a specific finish reason:

import { finishReasonIs } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Complete this task',
  tools: [taskTool],
  stopWhen: finishReasonIs('stop'), // Stop when model finishes naturally
});

Combining Conditions

Pass an array to stop on any condition:

import { stepCountIs, hasToolCall, maxCost } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5.2',
  input: 'Research thoroughly but stay within budget',
  tools: [searchTool, finishTool],
  stopWhen: [
    stepCountIs(10),        // Maximum 10 steps
    maxCost(0.50),          // Maximum $0.50
    hasToolCall('finish'),  // Or when finish is called
  ],
});

Execution stops when any condition is met.

Final Response After Stop

A stop condition can fire while the model is still emitting tool calls. By default, the SDK then executes those pending tool calls (so they have matching outputs) and makes one more model turn with toolChoice: 'none', appending a built-in final-answer directive (exported as DEFAULT_FINAL_RESPONSE_DIRECTIVE) as a user message — so the run ends with a real natural-language answer instead of a half-finished tool call. Tools stay in the request; only calling is forbidden, which preserves the prompt-cache prefix. Tune it with allowFinalResponse:

const result = openrouter.callModel({
  model: 'openai/gpt-5.2',
  input: 'Research this topic',
  tools: [searchTool],
  stopWhen: stepCountIs(5),
  // default (omitted or `true`): final turn + built-in directive

  // override the directive wording:
  // allowFinalResponse: 'Summarize what you found so far.',
  // make the final turn without appending any message:
  // allowFinalResponse: '',
  // disable the final turn (run ends on the halted tool-call turn):
  // allowFinalResponse: false,
});

Without the directive, models that emit tool-call syntax as text can leak an unparsed tool call (e.g. <tool_call>…) into the final content when the loop stops mid-tool-call. The default directive exists to prevent exactly that.

The final turn only happens when a stop condition halted the loop while the last response contained executable tool calls. It never fires on natural completion, HITL/approval pauses, or interruption.

Custom Stop Conditions

Create custom conditions with a function:

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Process data',
  tools: [processTool],
  stopWhen: ({ steps }) => {
    // Stop after 20 steps
    if (steps.length >= 20) return true;

    // Stop if last step had no tool calls
    const lastStep = steps[steps.length - 1];
    if (lastStep && !lastStep.toolCalls?.length) return true;

    // Continue otherwise
    return false;
  },
});

StopConditionContext

Custom functions receive:

Property	Type	Description
`steps`	`StepResult[]`	All completed steps including results and usage

StepResult

Each step contains:

interface StepResult {
  response: Response;
  toolCalls?: ParsedToolCall[];
  toolResults?: ToolExecutionResult[];
  tokens: {
    input: number;
    output: number;
    cached: number;
  };
  cost: number;
}

Advanced Patterns

Time-Based Stopping

Stop after a time limit:

const startTime = Date.now();
const maxDuration = 30000; // 30 seconds

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Work on this task',
  tools: [workTool],
  stopWhen: () => {
    return Date.now() - startTime > maxDuration;
  },
});

Content-Based Stopping

Stop based on response content:

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Search until you find the answer',
  tools: [searchTool],
  stopWhen: ({ steps }) => {
    const lastStep = steps[steps.length - 1];
    if (!lastStep) return false;

    // Check if response contains certain keywords
    const content = JSON.stringify(lastStep.response);
    return content.includes('ANSWER FOUND') || content.includes('TASK COMPLETE');
  },
});

Quality-Based Stopping

Stop when results meet quality threshold:

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Improve this text until it scores above 0.9',
  tools: [improverTool, scorerTool],
  stopWhen: ({ steps }) => {
    // Look for score in tool results
    for (const step of steps) {
      for (const result of step.toolResults ?? []) {
        if (result.toolName === 'scorer' && result.result?.score > 0.9) {
          return true;
        }
      }
    }
    return false;
  },
});

Combination with Early Exit

Combine conditions for complex logic:

import { stepCountIs, maxCost } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5.2',
  input: 'Complex research task',
  tools: [searchTool, analysisTool, summarizeTool],
  stopWhen: [
    // Hard limits
    stepCountIs(50),
    maxCost(5.00),

    // Custom success condition
    ({ steps }) => {
      const lastStep = steps[steps.length - 1];
      const hasSummary = lastStep?.toolCalls?.some(
        tc => tc.name === 'summarize'
      );
      return hasSummary;
    },
  ],
});

Migration from maxToolRounds

If you were using maxToolRounds, migrate to stopWhen:

// Before: maxToolRounds
const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Hello',
  tools: [myTool],
  maxToolRounds: 5,
});

// After: stopWhen
import { stepCountIs } from '@openrouter/agent';

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Hello',
  tools: [myTool],
  stopWhen: stepCountIs(5),
});

Default Behavior

If stopWhen is not specified, the loop runs until the model produces a turn with no tool calls. Always pass an explicit stopWhen (e.g. stepCountIs(n), maxCost(...)) to bound iterations, cost, or tokens.

Best Practices

Always Set Limits

Always include a hard limit to prevent runaway execution:

stopWhen: [
  stepCountIs(100),    // Hard limit
  maxCost(10.00),      // Budget limit
  customCondition,     // Your logic
],

Log Stop Reasons

Track why execution stopped:

const result = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Task',
  tools: [taskTool],
  stopWhen: ({ steps }) => {
    if (steps.length >= 10) {
      console.log('Stopped: step limit');
      return true;
    }
    const totalCost = steps.reduce((sum, step) => sum + (step.cost ?? 0), 0);
    if (totalCost >= 1.00) {
      console.log('Stopped: cost limit');
      return true;
    }
    return false;
  },
});

Test Conditions

Verify conditions work as expected:

// Test with low limits first
const testResult = openrouter.callModel({
  model: 'openai/gpt-5-nano',
  input: 'Test task',
  tools: [testTool],
  stopWhen: stepCountIs(2), // Low limit for testing
});

TypeScript SDK

Call Model

DevTools

Basic Usage

Built-in Stop Conditions

stepCountIs(n)

hasToolCall(name)

maxTokensUsed(n)

maxCost(amount)

finishReasonIs(reason)

Combining Conditions

Final Response After Stop

Custom Stop Conditions

StopConditionContext

StepResult

Advanced Patterns

Time-Based Stopping

Content-Based Stopping

Quality-Based Stopping

Combination with Early Exit

Migration from maxToolRounds

Default Behavior

Best Practices

Always Set Limits

Log Stop Reasons

Test Conditions

See Also

​Basic Usage

​Built-in Stop Conditions

​stepCountIs(n)

​hasToolCall(name)

​maxTokensUsed(n)

​maxCost(amount)

​finishReasonIs(reason)

​Combining Conditions

​Final Response After Stop

​Custom Stop Conditions

​StopConditionContext

​StepResult

​Advanced Patterns

​Time-Based Stopping

​Content-Based Stopping

​Quality-Based Stopping

​Combination with Early Exit

​Migration from maxToolRounds

​Default Behavior

​Best Practices

​Always Set Limits

​Log Stop Reasons

​Test Conditions

​See Also

Basic Usage

Built-in Stop Conditions

stepCountIs(n)

hasToolCall(name)

maxTokensUsed(n)

maxCost(amount)

finishReasonIs(reason)

Combining Conditions

Final Response After Stop

Custom Stop Conditions

StopConditionContext

StepResult

Advanced Patterns

Time-Based Stopping

Content-Based Stopping

Quality-Based Stopping

Combination with Early Exit

Migration from maxToolRounds

Default Behavior

Best Practices

Always Set Limits

Log Stop Reasons

Test Conditions

See Also