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Capture API response test fixture.
Passed 22 of 22 test cases with the skill, and 5 of 22 without it.
and 25 more in the full report
17 fixed5 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 17 test cases the skill fixed. Same model, same prompt, with and without the skill.
What exact pnpm CLI command should be executed from the /examples/ai-functions directory to run a streaming response capture script named mistral-large.ts for the mistral provider?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies running pnpm tsx src/stream-text/mistral/mistral-large.ts. | Missed | Passed |
The instructions your model reads when the skill loads.
For provider response parsing tests, we aim at storing test fixtures with the true responses from the providers (unless they are too large in which case some cutting that does not change semantics is advised).
The fixtures are stored in a __fixtures__ subfolder, e.g. packages/openai/src/responses/__fixtures__. See the file names in packages/openai/src/responses/__fixtures__ for naming conventions and packages/openai/src/responses/openai-responses-language-model.test.ts for how to set up test helpers.
You can use our examples under /examples/ai-functions to generate test fixtures.
For generateText, put the script under src/generate-text/<provider>/, log the raw response output to the console, and copy it into a new test fixture.
import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';
import { run } from '../../lib/run';
run(async () => {
const result = await generateText({
model: openai('gpt-5-nano'),
prompt: 'Invent a new holiday and describe its traditions.',
});
console.log(JSON.stringify(result.response.body, null, 2));
});
For streamText, you need to set includeRawChunks to true and use the special saveRawChunks helper. Put the script under the provider directory and run it from the /examples/ai-functions folder via pnpm tsx src/stream-text/<provider>/<script-name>.ts. The result is then stored in the /examples/ai-functions/output folder. You can copy it to your fixtures folder and rename it.
import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
import { run } from '../../lib/run';
import { saveRawChunks } from '../../lib/save-raw-chunks';
run(async () => {
const result = streamText({
model: openai('gpt-5-nano'),
test cases passed, vs 5 / 22 without
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