用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/s1366560/agi-demos --skill capture-api-response-test-fixture命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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Evidence-led triage and scoped recovery for local MemStack development runtime incidents. Use when FastAPI, React/Vite Web, Ray, the agent actor, Docker infrastructure, Redis, Postgres, Neo4j, the sandbox, or the Electron desktop sidecar fails to start, crashes, consumes abnormal resources, or becomes unresponsive.
Deliver and verify MemStack native desktop changes in agi-demos against the design-prototype or Web product surface while preserving the Electron shell, Rust sidecar, IPC, encrypted-vault, signing, and updater boundaries. Use for implementation, parity repair, or QA work scoped to agi-stack/apps/desktop; do not use for generic Web QA, mobile work, or unrelated desktop applications.
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基于 SOC 职业分类
| name | capture-api-response-test-fixture |
| description | Capture API response test fixture. |
| metadata | {"internal":true} |
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, 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. Run the script from the /example/ai-functions folder via pnpm tsx src/stream-text/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'),
prompt: 'Invent a new holiday and describe its traditions.',
includeRawChunks: true,
});
await saveRawChunks({ result, filename: 'openai-gpt-5-nano' });
});